# This is for normalized time scale
ticknames<-c(0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1)
tickvals <- c(0,1,2,3,4,5,6,7,8,9,10)
# For re-transformed real-time scale
ticknames1<-c(0, 20, 40, 60, 80, 100, 120, 140, 160)
tickvals1 <- c(0, 20, 40, 60, 80, 100, 120, 140, 160)
ticknames2<-c(0, 25, 50, 75, 100, 125, 150, 175, 200)
tickvals2<- c(0, 25, 50, 75, 100, 125, 150, 175, 200)The data used in the analysis are obtained from the corpus AISHELL-1 published by Beijing Shell Shell Technology Co.,Ltd. The recordings are conducted in a quiet indoor environment using a high fidelity microphone and downsampled to 16kHz. The sample used in the study are from 10 male speakers and 10 female speakers of Standard Mandarin. We obtained 4 sub-datasets, of two falling diphthongs /ai/ and /au/ by two genders.
[1] "t" "k" "p" "ʂ" "ʈʂ" "m" "n" "ts" "l" "ʐ" "ʔ" "s"
numero is the token number when extracting the data;
sex is the gender of the speaker; speaker is
the speaker ID; file is the audio file where the extracted
token from; measurement.no is the normalized time point
from 0 to 10; diphthong is what the
diphthong is; tone is the tone of this token (tone 3 sandhi
is transformed to tone 2); toneOri is the original tonal
category; tone.ord is the tone as the ordered factor value
(1<2<3<4); tonebis.ord is the reorganized ordered
factor value (4<1<2<3) (see Appendix B);
word is the word which the syllable belongs to;
leftTone is the pre-target tone; rightTone is
the post-target tone; initial is whether the character is
at the beginning of the sentence (in the current study, the value should
always be N); aspiration is whether the
segment at onset is aspirated (in this study, the value should
always be no); duration..ms. is the
duration of the diphthong in ms; f1, f2,
f0 are F1, F2, f0 in Hz;
durationZscore2, f1Zscore2,
f2Zscore2, f0Zscore2 are the values in
Z-score; start is whether the measurement point is at the
start point of all the 11 points (this is for the auto-regressive
modelling); posR is the relative position in the sentence;
wordPos, speakerPos,
wordLeftRightTone, speakerLeftRightTone are
word information and speaker information adjusted by posR and LeftTone
and RightTone.
[1] "numero" "sex" "speaker" "file" "measurement.no"
[6] "diphthong" "tone" "toneOri" "tone.ord" "toneBis.ord"
[11] "word" "leftTone" "rightTone" "initial" "aspiration"
[16] "duration..ms." "f1" "f2" "f0" "durationZscore2"
[21] "f1Zscore2" "f2Zscore2" "f0Zscore2" "start" "posR"
[26] "wordPos" "speakerPos" "speakerLeftRightTone" "wordLeftRightTone"
meanDurationZByTone <- aggregate(data.ai.mas$durationZscore2, by = list(tone = data.ai.mas$tone.ord),mean)# global mean values and standard deviations
## f0
global_mean0 <- mean(data.ai.mas$f0, na.rm = TRUE)
global_sd0 <- sd(data.ai.mas$f0, na.rm = TRUE)
## f1
global_mean1 <- mean(data.ai.mas$f1, na.rm = TRUE)
global_sd1 <- sd(data.ai.mas$f1, na.rm = TRUE)
## f2
global_mean2 <- mean(data.ai.mas$f2, na.rm = TRUE)
global_sd2 <- sd(data.ai.mas$f2, na.rm = TRUE)
## duration
global_meand <- mean(data.ai.mas$duration..ms., na.rm = TRUE)
global_sdd <- sd(data.ai.mas$duration..ms., na.rm = TRUE)
# print results
print(global_mean0)[1] 130.9548
[1] 23.29733
[1] 621.0464
[1] 107.4572
[1] 1684.322
[1] 152.3606
[1] 139.8406
[1] 40.63055
# reconstructed absolute duration of 4 tones
durationT1 <- meanDurationZByTone[1,2] * global_sdd + global_meand
durationT2 <- meanDurationZByTone[2,2] * global_sdd + global_meand
durationT3 <- meanDurationZByTone[3,2] * global_sdd + global_meand
durationT4 <- meanDurationZByTone[4,2] * global_sdd + global_meand
print(durationT1)[1] 148.2416
[1] 138.5754
[1] 137.0176
[1] 140.0018
meanDurationZByTonef <- aggregate(data.ai.fem$durationZscore2, by = list(tone = data.ai.fem$tone.ord),mean)# global mean values and standard deviations
## f0
global_mean0f <- mean(data.ai.fem$f0, na.rm = TRUE)
global_sd0f <- sd(data.ai.fem$f0, na.rm = TRUE)
## f1
global_mean1f <- mean(data.ai.fem$f1, na.rm = TRUE)
global_sd1f <- sd(data.ai.fem$f1, na.rm = TRUE)
## f2
global_mean2f <- mean(data.ai.fem$f2, na.rm = TRUE)
global_sd2f <- sd(data.ai.fem$f2, na.rm = TRUE)
## duration
global_meandf <- mean(data.ai.fem$duration..ms., na.rm = TRUE)
global_sddf <- sd(data.ai.fem$duration..ms., na.rm = TRUE)
# print results
print(global_mean0f)[1] 219.3686
[1] 33.53907
[1] 766.5056
[1] 157.2238
[1] 1896.827
[1] 218.7678
[1] 152.4137
[1] 32.45953
# reconstructed absolute duration of 4 tones
durationT1f <- meanDurationZByTonef[1,2] * global_sddf + global_meandf
durationT2f <- meanDurationZByTonef[2,2] * global_sddf + global_meandf
durationT3f <- meanDurationZByTonef[3,2] * global_sddf + global_meandf
durationT4f <- meanDurationZByTonef[4,2] * global_sddf + global_meandf
print(durationT1f)[1] 144.0195
[1] 156.5566
[1] 152.7313
[1] 151.7184
##/au/ male
meanDurationZByToneau <- aggregate(data.au.mas$durationZscore2, by = list(tone = data.au.mas$tone.ord),mean)# global mean values and standard deviations
## f0
global_mean0au <- mean(data.au.mas$f0, na.rm = TRUE)
global_sd0au <- sd(data.au.mas$f0, na.rm = TRUE)
## f1
global_mean1au <- mean(data.au.mas$f1, na.rm = TRUE)
global_sd1au <- sd(data.au.mas$f1, na.rm = TRUE)
## f2
global_mean2au <- mean(data.au.mas$f2, na.rm = TRUE)
global_sd2au <- sd(data.au.mas$f2, na.rm = TRUE)
## duration
global_meandau <- mean(data.au.mas$duration..ms., na.rm = TRUE)
global_sddau <- sd(data.au.mas$duration..ms., na.rm = TRUE)
# print results
print(global_mean0au)[1] 129.9584
[1] 24.0711
[1] 609.4632
[1] 94.02331
[1] 1175.144
[1] 171.9271
[1] 138.8545
[1] 35.32614
# reconstructed absolute duration of 4 tones
durationT1au <- meanDurationZByToneau[1,2] * global_sddau + global_meandau
durationT2au <- meanDurationZByToneau[2,2] * global_sddau + global_meandau
durationT3au <- meanDurationZByToneau[3,2] * global_sddau + global_meandau
durationT4au <- meanDurationZByToneau[4,2] * global_sddau + global_meandau
print(durationT1au)[1] 149.8533
[1] 138.4197
[1] 130.7606
[1] 139.0956
meanDurationZByToneauf <- aggregate(data.au.fem$durationZscore2, by = list(tone = data.au.fem$tone.ord),mean)# global mean values and standard deviations
## f0
global_mean0auf <- mean(data.au.fem$f0, na.rm = TRUE)
global_sd0auf <- sd(data.au.fem$f0, na.rm = TRUE)
## f1
global_mean1auf <- mean(data.au.fem$f1, na.rm = TRUE)
global_sd1auf <- sd(data.au.fem$f1, na.rm = TRUE)
## f2
global_mean2auf <- mean(data.au.fem$f2, na.rm = TRUE)
global_sd2auf <- sd(data.au.fem$f2, na.rm = TRUE)
## duration
global_meandauf <- mean(data.au.fem$duration..ms., na.rm = TRUE)
global_sddauf <- sd(data.au.fem$duration..ms., na.rm = TRUE)
# print results
print(global_mean0auf)[1] 223.0908
[1] 33.08992
[1] 751.3295
[1] 127.0412
[1] 1348.953
[1] 191.1671
[1] 158.5503
[1] 30.91023
# reconstructed absolute duration of 4 tones
durationT1auf <- meanDurationZByToneauf[1,2] * global_sddauf + global_meandauf
durationT2auf <- meanDurationZByToneauf[2,2] * global_sddauf + global_meandauf
durationT3auf <- meanDurationZByToneauf[3,2] * global_sddauf + global_meandauf
durationT4auf <- meanDurationZByToneauf[4,2] * global_sddauf + global_meandauf
print(durationT1auf)[1] 159.5236
[1] 163.6863
[1] 153.0105
[1] 159.554
gamm.model1a.noAR <- bam(f1Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.ai.mas, method="fREML", discrete = TRUE, nthreads = ncores)# Auto-regressive model
gamm.model1a <- bam(f1Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.ai.mas, method="fREML", rho = r.gamm.model1a, AR.start = data.ai.mas$start, discrete = TRUE, nthreads = ncores)
Family: gaussian
Link function: identity
Formula:
f1Zscore2 ~ toneBis.ord + s(measurement.no, bs = "cr") + s(measurement.no,
by = toneBis.ord, bs = "cr") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speaker, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = toneBis.ord) + s(measurement.no, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1, by = toneBis.ord) + s(measurement.no, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerPos, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = toneBis.ord) + s(measurement.no, word, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordPos, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 3, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.13798 0.04700 2.936 0.00334 **
toneBis.ord1 -0.43108 0.16979 -2.539 0.01113 *
toneBis.ord2 0.08773 0.09831 0.892 0.37223
toneBis.ord3 0.03179 0.11072 0.287 0.77402
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 7.805 8.046 69.293 <2e-16 ***
s(measurement.no):toneBis.ord1 2.093 2.662 0.741 0.5883
s(measurement.no):toneBis.ord2 7.016 7.863 9.458 <2e-16 ***
s(measurement.no):toneBis.ord3 3.813 4.531 2.577 0.0272 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.64 Deviance explained = 67.4%
fREML = 9248.7 Scale est. = 0.30499 n = 12023
Method: fREML Optimizer: perf chol
$grad
[1] 4.041212e-14 -2.884692e-12 -9.547918e-14 -2.406964e-13 -1.030642e-11 -5.341571e-05 -9.061204e-05 -9.884080e-05 -4.978977e-05
[10] 7.482903e-14 -5.014362e-05 -4.804637e-05 -1.836753e-11 6.714629e-13 -8.126086e-05 -1.823430e-12 -1.267253e-11 -1.749711e-13
[19] 6.743051e-12 1.731948e-13 -5.776357e-11 -2.247091e-13 -4.232951e-05 -1.195044e-12 -4.256151e-12 -3.446132e-13 -4.647838e-12
[28] 2.144951e-13 -9.968915e-11 5.329071e-14 -8.219914e-11 4.916956e-12 -1.794973e-10 -6.252776e-13 1.289663e-09
$hess
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
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1.731180e-03 -3.290458e-08 1.621072e-07 1.384428e-03 7.006297e-03 6.870456e-07 2.411514e-01 -7.747128e-04 -1.822861e-03
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4.292356e-01 1.005476e-07 9.305561e-07 2.052212e-03 5.520382e-02 6.316423e-08 1.110856e-02 -1.591250e-02 4.165585e-02
1.783067e-04 1.861471e-05 -6.765457e-08 4.274393e-02 -1.099702e-03 3.508441e-07 -1.096266e-03 1.273165e-02 -1.664953e-04
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[,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26] [,27]
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6.073223e-01 5.459726e-04 1.486508e-02 2.825477e-03 2.612542e-08 -6.388198e-04 -2.015045e-02 3.170395e-03 1.052083e+00
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[,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35]
5.134865e-06 6.397193e-03 -3.881823e-04 -7.318165e-04 -2.462069e-04 1.101810e-02 -1.270744e-03 -3.402498e+00
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2.647251e-06 2.031523e-02 -1.859782e-03 8.025038e-04 -1.340330e-03 -1.486732e-02 -2.903254e-03 -3.007914e+00
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9.322316e-03 -3.243691e-03 2.762248e-02 -3.788045e-04 1.269557e-01 -1.260627e-03 -6.142758e-02 -4.671427e+00
8.798651e-04 4.186766e-01 1.684687e-03 1.657153e-02 -9.174442e-05 7.222583e-01 -7.916400e-03 -2.320523e+01
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-1.372430e-02 -2.586328e-02 -1.853680e-03 -2.111150e-02 -4.733460e-03 3.344158e-01 1.086730e-02 -3.682817e+01
-1.379502e-01 -1.376107e-02 6.899110e-02 -5.329938e-04 3.404328e-01 -3.567675e-02 -2.515323e-01 -6.715082e+00
-3.114564e-03 1.872148e-01 -5.416453e-03 1.451644e-01 -2.333628e-02 2.134095e-01 -2.663004e-02 -1.869814e+01
-1.439501e-01 -4.117005e-03 -4.954632e-02 1.360726e-03 -4.579150e-03 5.629381e-03 2.531043e-02 -7.720738e+00
5.252809e-09 -1.823139e-07 1.215848e-08 4.940700e-07 -2.520812e-07 -2.782813e-06 2.810575e-08 -8.234459e-05
1.533555e-03 -2.622506e-04 5.478100e-02 2.969339e-04 1.417136e-01 1.052615e-03 1.003159e-01 -1.715349e+00
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-3.354339e-02 -8.240811e-02 -4.419511e-03 1.417983e-02 -2.291816e-02 6.337225e-02 -1.076768e-02 -7.568868e+00
2.619163e-01 -1.003260e-03 5.591196e-02 -4.582528e-04 3.074007e-01 -3.332089e-03 2.035330e-01 -1.713075e+00
[ getOption("max.print") est atteint -- 7 lignes omises ]
Model rank = 6565 / 6565
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00e+00 7.80e+00 1 0.47
s(measurement.no):toneBis.ord1 9.00e+00 2.09e+00 1 0.51
s(measurement.no):toneBis.ord2 9.00e+00 7.02e+00 1 0.51
s(measurement.no):toneBis.ord3 9.00e+00 3.81e+00 1 0.46
s(measurement.no,speaker) 1.00e+02 5.82e+01 1 0.47
s(measurement.no,speaker):toneBis.ord1 1.00e+02 2.02e-03 1 0.49
s(measurement.no,speaker):toneBis.ord2 1.00e+02 3.32e+00 1 0.51
s(measurement.no,speaker):toneBis.ord3 1.00e+02 1.03e-03 1 0.54
s(measurement.no,speakerLeftRightTone) 5.90e+02 9.51e+01 1 0.49
s(measurement.no,speakerLeftRightTone):toneBis.ord1 5.90e+02 9.34e+00 1 0.59
s(measurement.no,speakerLeftRightTone):toneBis.ord2 5.90e+02 6.15e+01 1 0.50
s(measurement.no,speakerLeftRightTone):toneBis.ord3 5.90e+02 8.71e+01 1 0.52
s(measurement.no,speakerPos) 3.00e+02 5.28e+01 1 0.54
s(measurement.no,speakerPos):toneBis.ord1 3.00e+02 3.43e+00 1 0.54
s(measurement.no,speakerPos):toneBis.ord2 3.00e+02 6.35e+01 1 0.51
s(measurement.no,speakerPos):toneBis.ord3 3.00e+02 1.86e+01 1 0.52
s(measurement.no,word) 6.30e+02 1.55e+02 1 0.53
s(measurement.no,wordPos) 9.99e+02 9.50e+01 1 0.52
s(measurement.no,wordLeftRightTone) 9.36e+02 4.16e+02 1 0.53
# Plotting
# Normalized scale
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model1a, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", ylim = c(-1, 1), lwd = 4, xlab = "Time (normalized)", ylab = "F1 (Z)", xaxt = "n", font.lab = 2)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1a, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"), col = "orange", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1a, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"), col = "chartreuse4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1a, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"), col = "royalblue4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
legend("topright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)# Plotting
# Reconstructed scale
# output: 1000 dpi png
# png("pred1-1t.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model1a, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", ylim = c(500, 800), xlab = "Time (ms)", ylab = "F1 (Hz)", xaxt = "n", font.lab = 2, add = F, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT1 * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1 + global_mean1, hide.label = TRUE)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1a, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"), col = "orange", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT2 * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1 + global_mean1)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1a, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"), col = "chartreuse4", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT3 * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1 + global_mean1)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1a, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"), col = "royalblue4", lwd = 4, add = T, transform.view = function(measurement.no) measurement.no * durationT4 * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1 + global_mean1)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
legend("topright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)# Plotting
# Difference plot between tones
par(mfcol = c(2, 3), mar = c(2, 2, 2, 1), oma = c(4, 4, 2, 1))
plot_diff(gamm.model1a, view="measurement.no", comp=list(toneBis.ord = c("1","2")), rm.ranef=TRUE, main = "1-2", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.000000 - 7.474747
plot_diff(gamm.model1a, view="measurement.no",comp=list(toneBis.ord = c("1","3")),rm.ranef=TRUE, main = "1-3", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.505051 - 6.666667
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
plot_diff(gamm.model1a, view="measurement.no",comp=list(toneBis.ord = c("1","4")),rm.ranef=TRUE, main = "1-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.000000 - 10.000000
plot_diff(gamm.model1a, view="measurement.no",comp=list(toneBis.ord = c("2","3")),rm.ranef=TRUE, main = "2-3", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
plot_diff(gamm.model1a, view="measurement.no",comp=list(toneBis.ord = c("2","4")),rm.ranef=TRUE, main = "2-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.505051 - 4.141414
9.393939 - 10.000000
plot_diff(gamm.model1a, view="measurement.no",comp=list(toneBis.ord = c("3","4")),rm.ranef=TRUE, main = "3-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
mtext("Difference in F1 (Z)", side = 2, outer = TRUE, line = 2.5, cex = 1.2, font = 2)plot_parametric(gamm.model1a, pred = list(toneBis.ord=c("1", "2", "3", "4")), main = "Tone", xlab = "F1 (Z)")Summary:
* toneBis.ord : factor; set to the value(s): 1, 2, 3, 4.
* measurement.no : numeric predictor; set to the value(s): 5.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
gamm.model1b.noAR <- bam(f1Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.ai.fem, method="fREML", discrete = TRUE, nthreads = ncores)# Auto-regressive model
gamm.model1b <- bam(f1Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.ai.fem, method="fREML", rho = r.gamm.model1b, AR.start = data.ai.fem$start, discrete = TRUE, nthreads = ncores)
Family: gaussian
Link function: identity
Formula:
f1Zscore2 ~ toneBis.ord + s(measurement.no, bs = "cr") + s(measurement.no,
by = toneBis.ord, bs = "cr") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speaker, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = toneBis.ord) + s(measurement.no, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1, by = toneBis.ord) + s(measurement.no, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerPos, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = toneBis.ord) + s(measurement.no, word, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordPos, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 3, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.26984 0.05890 4.581 4.68e-06 ***
toneBis.ord1 -0.48869 0.17880 -2.733 0.00628 **
toneBis.ord2 0.04083 0.09876 0.413 0.67933
toneBis.ord3 0.04743 0.10469 0.453 0.65050
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 7.797 7.971 89.711 < 2e-16 ***
s(measurement.no):toneBis.ord1 1.001 1.001 0.028 0.86825
s(measurement.no):toneBis.ord2 7.300 7.841 6.282 < 2e-16 ***
s(measurement.no):toneBis.ord3 4.857 5.606 3.375 0.00424 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.771 Deviance explained = 79.7%
fREML = 6300.4 Scale est. = 0.19144 n = 11198
Method: fREML Optimizer: perf chol
$grad
[1] 2.355005e-12 -8.137698e-05 -1.851852e-13 3.777201e-12 -4.923351e-11 -4.879585e-05 -4.059321e-05 -1.375344e-12 -1.144684e-11
[10] 4.327649e-13 -1.660183e-11 -8.174095e-05 -2.022915e-10 -9.237056e-14 -4.430824e-09 6.265921e-11 1.762146e-11 8.757439e-13
[19] -1.168843e-12 -4.153122e-12 1.362466e-11 2.014389e-12 -4.909594e-05 -7.184224e-05 -5.618617e-12 -4.156675e-13 -2.515321e-12
[28] -9.318935e-14 -1.172111e-10 -1.527667e-12 -1.002221e-10 -3.694822e-13 -8.341772e-11 2.131628e-12 7.228664e-09
$hess
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
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[,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18]
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2.602601e-08 1.984711e-06 9.956430e-12 6.355302e-06 -8.329858e-08 1.307646e-05 1.565759e-08 -5.084830e-07 7.859647e-08
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1.379214e-04 -1.081056e-01 -1.262544e-07 8.527338e+00 -8.190319e-02 3.099895e-01 -4.756327e-03 9.156217e-01 1.364860e-02
9.499431e-02 8.082037e-03 -1.508594e-05 -8.190319e-02 6.810330e+00 -6.597013e-05 -1.737594e-01 -1.576030e-03 1.701012e+00
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6.543495e-03 1.768535e-03 -2.629687e-06 -4.756327e-03 -1.737594e-01 -7.959894e-02 3.001638e+00 2.267123e-03 -7.995519e-03
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3.983100e-01 -8.990342e-04 -1.503728e-05 1.364860e-02 1.701012e+00 -1.094120e-03 -7.995519e-03 -1.249457e-01 5.481277e+00
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3.228192e-03 9.070257e-02 4.847512e-07 5.198314e-01 -1.976906e-02 3.254096e-03 -5.663102e-03 1.563297e-01 1.833771e-03
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2.941717e-01 1.252069e-04 -1.045957e-06 -2.191842e-04 -4.032050e-02 7.991828e-04 -3.501802e-02 -1.646201e-02 -3.063455e-02
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-4.770183e-04 -2.733978e-04 2.080351e-06 -3.624303e-05 4.232058e-03 7.185098e-05 -1.942619e-04 -8.952064e-05 -1.754698e-03
[,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26] [,27]
-1.499063e-03 5.211523e-05 -2.301350e-02 3.503530e-05 -1.247481e-07 1.996622e-08 1.076177e-03 -7.351581e-05 3.603762e-04
1.138373e-06 4.511044e-08 -1.126469e-05 1.079398e-07 2.822664e-10 3.467387e-11 1.410646e-06 2.359124e-08 2.021176e-07
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-7.183592e-02 2.152288e-03 3.243855e-02 7.873861e-05 -1.003524e-07 8.543162e-08 3.076541e-04 -3.928286e-04 5.645724e-02
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3.050479e+00 8.247993e-02 -2.082275e-02 1.275849e-03 -5.567415e-07 2.037004e-07 -4.574614e-03 1.482445e-03 3.809748e-01
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[,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35]
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-4.770183e-04 6.047906e-03 -2.688093e-02 1.954468e-03 -1.923574e-03 6.194074e-03 7.054727e-02 -1.959279e+00
-2.733978e-04 -8.459636e-02 1.046164e-02 1.196766e-01 -1.404408e-02 -6.377852e-02 6.315453e-03 -8.971754e+00
2.080351e-06 4.401494e-07 -5.520421e-05 -7.427578e-07 2.978219e-05 8.652885e-07 -6.137451e-06 -2.826292e-04
-3.624303e-05 9.323632e-01 4.698917e-03 5.625916e-01 4.619305e-03 3.012858e+00 -6.138344e-03 -3.764725e+01
4.232058e-03 4.373885e-02 3.747390e+00 1.127466e-02 1.083238e+00 4.967543e-02 5.568526e+00 -2.271341e+01
7.185098e-05 1.289479e-01 3.037234e-03 1.433014e-01 3.544926e-04 6.865017e-02 -1.403029e-03 -8.711404e+00
-1.942619e-04 -3.758715e-04 -4.129769e-02 -9.751264e-04 -9.994131e-02 5.227153e-03 2.487336e-02 -5.281231e+00
-8.952064e-05 5.665497e-01 -5.547123e-03 3.485268e-02 2.457342e-03 1.102789e+00 -1.143414e-04 -3.549148e+01
-1.754698e-03 8.422340e-04 -5.197211e-01 -6.649523e-03 -5.139187e-01 -3.612642e-02 -4.957946e-01 -1.203109e+01
6.335997e-05 1.111576e-01 9.646000e-03 3.378472e-01 -5.855717e-03 -2.432590e-02 3.665522e-03 -1.662720e+01
1.730895e-02 9.250286e-03 -6.560844e-01 -1.824690e-04 9.562812e-03 -1.831421e-02 -6.251386e-01 -9.175892e+00
2.780325e-04 9.945617e-02 9.242423e-03 3.256043e-02 -1.061381e-02 3.016209e-01 -9.741670e-03 -3.164751e+01
3.992384e-03 2.645248e-03 1.127626e-01 5.492350e-03 -5.203557e-01 -4.624418e-03 2.827055e-02 -6.367651e+00
2.957308e-09 6.934881e-06 9.372916e-08 1.130848e-05 -1.215490e-07 4.211097e-06 -7.804410e-08 -3.477411e-04
1.889700e-07 -1.149069e-06 2.028897e-05 3.436174e-07 3.525361e-06 -6.453213e-06 1.122015e-04 -1.092900e-03
-2.844252e-05 1.292142e-01 2.840407e-03 4.025624e-02 -3.553123e-03 2.960472e-01 -1.347774e-02 -1.136728e+01
-3.138603e-04 4.838612e-03 1.321379e-02 -5.882335e-03 1.735786e-02 1.155861e-02 -9.853477e-02 -5.040649e+00
1.387570e-03 2.223193e-01 1.340519e-03 1.920210e-01 1.640177e-02 2.777977e-01 -6.187345e-03 -1.184315e+01
2.078162e-03 -3.044769e-05 -1.032302e-03 7.814940e-04 1.162611e-02 3.874255e-04 8.491506e-03 -1.115762e-01
[ getOption("max.print") est atteint -- 7 lignes omises ]
Model rank = 6427 / 6427
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00e+00 7.80e+00 1 0.64
s(measurement.no):toneBis.ord1 9.00e+00 1.00e+00 1 0.55
s(measurement.no):toneBis.ord2 9.00e+00 7.30e+00 1 0.52
s(measurement.no):toneBis.ord3 9.00e+00 4.86e+00 1 0.52
s(measurement.no,speaker) 1.00e+02 6.56e+01 1 0.66
s(measurement.no,speaker):toneBis.ord1 1.00e+02 2.77e+00 1 0.56
s(measurement.no,speaker):toneBis.ord2 1.00e+02 3.52e+01 1 0.55
s(measurement.no,speaker):toneBis.ord3 1.00e+02 1.79e+01 1 0.51
s(measurement.no,speakerLeftRightTone) 5.90e+02 1.21e+02 1 0.59
s(measurement.no,speakerLeftRightTone):toneBis.ord1 5.90e+02 2.80e+01 1 0.59
s(measurement.no,speakerLeftRightTone):toneBis.ord2 5.90e+02 9.50e+01 1 0.55
s(measurement.no,speakerLeftRightTone):toneBis.ord3 5.90e+02 5.16e+01 1 0.56
s(measurement.no,speakerPos) 3.00e+02 7.60e+01 1 0.60
s(measurement.no,speakerPos):toneBis.ord1 3.00e+02 3.12e-03 1 0.51
s(measurement.no,speakerPos):toneBis.ord2 3.00e+02 3.28e+01 1 0.65
s(measurement.no,speakerPos):toneBis.ord3 3.00e+02 2.39e+01 1 0.59
s(measurement.no,word) 6.15e+02 2.59e+02 1 0.56
s(measurement.no,wordPos) 9.33e+02 1.71e+02 1 0.56
s(measurement.no,wordLeftRightTone) 8.79e+02 2.80e+02 1 0.55
# Plotting
# Normalized scale
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model1b, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"), col = "orange", ylim = c(-1, 1), lwd = 4, xlab = "Time (normalized)", ylab = "F1 (Z)", xaxt = "n", font.lab = 2)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1b, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1b, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"), col = "chartreuse4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1b, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"), col = "royalblue4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
legend("topright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)# Plotting
# Reconstructed scale
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model1b, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"), col = "orange", ylim = c(500, 1000), xlab = "Time (ms)", ylab = "F1 (Hz)", xaxt = "n", font.lab = 2, add = F, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT2f * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1f + global_mean1f, hide.label = TRUE)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1b, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", lwd = 4, add = T, transform.view = function(measurement.no) measurement.no * durationT1f * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1f + global_mean1f)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1b, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"), col = "royalblue4", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT4f * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1f + global_mean1f)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1b, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"), col = "chartreuse4", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT3f * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1f + global_mean1f)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
legend("topright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)# Plotting
# Difference plot between tones
par(mfcol = c(2, 3), mar = c(2, 2, 2, 1), oma = c(4, 4, 2, 1))
plot_diff(gamm.model1b, view="measurement.no", comp=list(toneBis.ord = c("1","2")),rm.ranef=TRUE, main = "1-2", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.000000 - 7.575758
#axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
plot_diff(gamm.model1b, view="measurement.no",comp=list(toneBis.ord = c("1","3")),rm.ranef=TRUE, main = "1-3", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
1.010101 - 9.494949
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
plot_diff(gamm.model1b, view="measurement.no",comp=list(toneBis.ord = c("1","4")),rm.ranef=TRUE, main = "1-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.000000 - 10.000000
#axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
plot_diff(gamm.model1b, view="measurement.no",comp=list(toneBis.ord = c("2","3")),rm.ranef=TRUE, main = "2-3", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.707071 - 1.111111
plot_diff(gamm.model1b, view="measurement.no",comp=list(toneBis.ord = c("2","4")),rm.ranef=TRUE, main = "2-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.505051 - 2.222222
#axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
plot_diff(gamm.model1b, view="measurement.no",comp=list(toneBis.ord = c("3","4")),rm.ranef=TRUE, main = "3-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
mtext("Difference in F1 (Z)", side = 2, outer = TRUE, line = 2.5, cex = 1.2, font = 2)plot_parametric(gamm.model1b, pred = list(toneBis.ord=c("1", "2", "3", "4")), main = "Tone", xlab = "F1 (Z)")Summary:
* toneBis.ord : factor; set to the value(s): 1, 2, 3, 4.
* measurement.no : numeric predictor; set to the value(s): 5.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
gamm.model1c.noAR <- bam(f1Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.au.mas, method="fREML", discrete = TRUE, nthreads = ncores)# Auto-regressive model
gamm.model1c <- bam(f1Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.au.mas, method="fREML", rho = r.gamm.model1c, AR.start = data.au.mas$start, discrete = TRUE, nthreads = ncores)
Family: gaussian
Link function: identity
Formula:
f1Zscore2 ~ toneBis.ord + s(measurement.no, bs = "cr") + s(measurement.no,
by = toneBis.ord, bs = "cr") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speaker, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = toneBis.ord) + s(measurement.no, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1, by = toneBis.ord) + s(measurement.no, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerPos, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = toneBis.ord) + s(measurement.no, word, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordPos, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 3, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.060211 0.055331 1.088 0.276537
toneBis.ord1 -0.442326 0.091890 -4.814 1.51e-06 ***
toneBis.ord2 0.006794 0.091474 0.074 0.940793
toneBis.ord3 0.312667 0.081333 3.844 0.000122 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 7.670 8.032 64.474 <2e-16 ***
s(measurement.no):toneBis.ord1 3.091 3.802 2.286 0.0513 .
s(measurement.no):toneBis.ord2 1.000 1.000 2.899 0.0887 .
s(measurement.no):toneBis.ord3 3.533 4.096 2.729 0.0266 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.657 Deviance explained = 70.9%
fREML = 10543 Scale est. = 0.32426 n = 10857
Method: fREML Optimizer: perf chol
$grad
[1] 9.681145e-14 -1.776357e-14 -5.014119e-05 -1.232348e-13 0.000000e+00 -4.773879e-05 -9.651113e-05 -4.919213e-05 -7.603781e-05
[10] -9.746363e-05 -9.508623e-05 -9.405792e-05 -3.765876e-13 -2.202682e-13 3.046452e-13 -1.048051e-13 1.376677e-13 -9.797667e-05
[19] 1.705303e-13 -2.309264e-14 6.750156e-14 -5.329071e-14 4.618528e-14 4.973799e-14 7.105427e-15 -4.810617e-05 1.456613e-13
[28] 1.127987e-13 7.105427e-14 1.037392e-12 3.410605e-13 4.263256e-13 3.694822e-13 -1.989520e-13 4.547474e-12
$hess
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
3.462193e+00 -1.137325e-02 2.190058e-06 4.961225e-02 -3.299671e-02 3.034639e-10 -1.601364e-06 -1.059766e-07 -1.905974e-07
-1.137325e-02 7.165497e-01 8.770145e-06 -8.565477e-03 -3.409280e-02 3.928110e-09 4.405821e-06 2.557979e-07 6.709955e-07
2.190058e-06 8.770145e-06 5.015151e-05 -1.162515e-06 6.877865e-06 -8.786020e-12 -1.388045e-10 3.015069e-11 3.691683e-10
4.961225e-02 -8.565477e-03 -1.162515e-06 5.975867e-01 -1.085729e-02 -1.070045e-08 9.489704e-07 -2.866613e-08 6.375498e-07
-3.299671e-02 -3.409280e-02 6.877865e-06 -1.085729e-02 1.136755e+01 -1.040605e-07 1.266081e-05 -4.021332e-06 1.595450e-05
3.034639e-10 3.928110e-09 -8.786020e-12 -1.070045e-08 -1.040605e-07 4.774418e-05 -9.201469e-12 -2.021643e-08 -4.675430e-12
-1.601364e-06 4.405821e-06 -1.388045e-10 9.489704e-07 1.266081e-05 -9.201469e-12 9.652650e-05 2.090843e-09 -1.368250e-10
-1.059766e-07 2.557979e-07 3.015069e-11 -2.866613e-08 -4.021332e-06 -2.021643e-08 2.090843e-09 6.114258e-05 -2.836031e-10
-1.905974e-07 6.709955e-07 3.691683e-10 6.375498e-07 1.595450e-05 -4.675430e-12 -1.368250e-10 -2.836031e-10 7.604259e-05
-6.461417e-09 -3.339083e-09 -3.010039e-11 7.812958e-09 4.948893e-08 -2.882737e-10 -2.544260e-12 -5.151366e-09 -2.826756e-11
1.658825e-06 2.316011e-07 1.950866e-10 1.054927e-05 -3.005954e-05 -4.152255e-12 2.043134e-10 2.765375e-11 6.381021e-11
-1.185780e-08 8.986651e-08 -2.662848e-11 -1.803007e-07 2.231221e-06 -1.277243e-08 -5.635538e-11 2.693756e-08 1.804706e-11
-3.902424e-02 3.928589e-02 -1.283390e-05 1.435327e-03 2.311166e+00 -3.138625e-07 2.727351e-06 -1.025585e-05 5.034014e-06
-1.084292e-03 7.067769e-05 9.671237e-09 -6.501510e-04 -1.721403e-03 5.485718e-05 -1.151871e-07 -6.720659e-04 2.549189e-07
-2.301347e-03 2.187482e-02 -4.970189e-08 2.126738e-03 1.201095e-02 9.626930e-09 2.978077e-05 1.308316e-06 -1.200650e-07
-8.358042e-05 1.642326e-04 1.237021e-08 -9.268128e-06 1.168928e-03 -4.752375e-06 5.296669e-07 2.028409e-03 1.479344e-07
-6.800272e-03 1.899594e-03 -4.565243e-06 1.394357e-02 1.095966e-01 -3.464066e-08 -1.244823e-07 -1.655263e-06 3.196528e-05
-2.752269e-11 2.697647e-09 -2.787166e-12 4.287188e-09 4.705936e-08 -1.709127e-10 -6.774337e-13 1.289242e-10 -2.199913e-12
4.770773e-02 1.085158e-02 -2.860897e-07 1.282609e-01 -6.229080e-01 -3.956074e-08 1.627322e-06 -7.930093e-07 2.448632e-06
-1.977190e-04 2.066826e-04 -3.862087e-08 -7.248829e-04 3.348742e-03 -9.762976e-06 -5.757055e-08 2.384311e-04 -4.479960e-07
-1.343996e-02 -1.933901e-03 2.930288e-06 7.188260e-03 1.661145e+00 -3.937988e-08 7.578434e-06 2.148657e-06 4.615502e-06
-4.175626e-05 -2.101576e-04 -8.880872e-09 2.622473e-05 7.348834e-04 2.890917e-05 -1.242873e-07 2.482589e-05 -2.224812e-07
-9.111643e-03 6.695449e-02 -1.554034e-06 5.871734e-03 3.604937e-02 -6.445434e-08 1.026974e-04 4.622120e-06 -1.045842e-06
-6.853272e-05 2.821799e-04 -1.037149e-08 9.065814e-07 -3.353190e-04 -4.377071e-06 2.009601e-07 4.006969e-03 -1.215765e-08
-7.935187e-03 1.563530e-02 -2.224423e-06 2.513018e-02 3.115543e-01 1.865849e-07 -4.243435e-06 -6.480917e-06 1.123289e-04
2.606433e-10 1.204878e-09 6.592714e-13 1.075133e-09 -1.999768e-09 -4.865325e-11 7.665352e-14 -1.229003e-09 -4.183841e-12
6.499681e-03 -4.337589e-03 2.201209e-06 1.410892e-02 -6.364897e-02 -3.788359e-08 1.781038e-06 -5.354775e-07 1.069530e-06
-1.745212e-05 1.488390e-04 -1.441488e-07 1.126533e-04 1.484850e-03 -3.247099e-06 -5.826576e-08 6.727364e-06 1.530749e-07
[,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18]
-6.461417e-09 1.658825e-06 -1.185780e-08 -3.902424e-02 -1.084292e-03 -2.301347e-03 -8.358042e-05 -6.800272e-03 -2.752269e-11
-3.339083e-09 2.316011e-07 8.986651e-08 3.928589e-02 7.067769e-05 2.187482e-02 1.642326e-04 1.899594e-03 2.697647e-09
-3.010039e-11 1.950866e-10 -2.662848e-11 -1.283390e-05 9.671237e-09 -4.970189e-08 1.237021e-08 -4.565243e-06 -2.787166e-12
7.812958e-09 1.054927e-05 -1.803007e-07 1.435327e-03 -6.501510e-04 2.126738e-03 -9.268128e-06 1.394357e-02 4.287188e-09
4.948893e-08 -3.005954e-05 2.231221e-06 2.311166e+00 -1.721403e-03 1.201095e-02 1.168928e-03 1.095966e-01 4.705936e-08
-2.882737e-10 -4.152255e-12 -1.277243e-08 -3.138625e-07 5.485718e-05 9.626930e-09 -4.752375e-06 -3.464066e-08 -1.709127e-10
-2.544260e-12 2.043134e-10 -5.635538e-11 2.727351e-06 -1.151871e-07 2.978077e-05 5.296669e-07 -1.244823e-07 -6.774337e-13
-5.151366e-09 2.765375e-11 2.693756e-08 -1.025585e-05 -6.720659e-04 1.308316e-06 2.028409e-03 -1.655263e-06 1.289242e-10
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[,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26] [,27]
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1.243523e+00 -1.617912e-03 1.600251e-02 -1.859622e-03 -2.002501e-02 -4.062657e-07 5.812132e-02 -1.994496e-08 2.421344e+00
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[,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35]
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1.484850e-03 -3.492194e-02 -1.918000e-04 -9.375976e-02 -1.558337e-03 -5.439919e-02 -3.417869e-04 -1.923601e+01
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1.530749e-07 -2.616508e-06 1.061744e-07 6.628547e-06 -5.070010e-08 4.828187e-07 1.804501e-07 -4.386036e-04
2.737885e-06 -2.672274e-08 1.133633e-06 -1.171547e-07 -1.085175e-05 -1.680063e-07 -2.984472e-05 -7.142378e-05
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3.428581e-04 8.893011e-07 5.857168e-05 2.865924e-06 5.802056e-04 1.071035e-06 -2.763050e-04 -2.605385e-03
1.557291e-03 1.586671e+00 -3.409431e-04 1.224802e+00 -1.578324e-03 7.357650e+00 -8.204265e-03 -5.987854e+01
4.989887e-02 -5.537058e-03 1.463651e-01 -6.000875e-03 -1.844886e-01 -2.148919e-02 4.863955e+00 -2.140589e+01
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5.026723e-02 -3.398816e-03 -4.013640e-02 -1.580185e-03 -1.308629e-02 -7.266771e-03 -1.339855e-01 -8.612105e+00
1.216896e-03 2.046038e-01 -1.286860e-04 2.672029e-01 -4.576968e-04 3.382203e-01 -2.216111e-03 -6.115421e+00
1.071718e-06 -2.787125e-08 -3.605416e-06 -4.352495e-08 -2.179201e-05 -3.075142e-08 -2.106535e-05 -6.610294e-05
-3.335378e-03 1.165285e+00 2.881074e-05 2.344594e+00 2.675007e-02 1.345475e+00 9.786980e-03 -7.893145e+01
8.666964e-01 3.878495e-03 -5.850941e-03 -4.293601e-03 1.477834e+00 1.449560e-02 -1.886093e-01 -1.404010e+01
1.443970e-03 -3.627841e-02 -1.818683e-05 -1.630241e-01 -2.907367e-03 -3.827110e-01 -3.012385e-03 -2.082925e+01
3.468851e-02 6.373469e-04 -1.267363e-01 1.523656e-04 -8.546051e-01 -3.760326e-03 -8.728003e-01 -9.027570e+00
-1.473467e-03 1.934407e-01 -4.226946e-05 2.078162e-01 1.718289e-03 6.697884e-01 -1.164509e-03 -1.339107e+01
1.383896e-01 5.182333e-04 -4.928362e-02 -1.290755e-03 1.153150e-01 1.040919e-03 -9.274989e-01 -6.860890e+00
7.312562e-03 3.106654e-01 -2.499850e-03 4.053729e-01 -1.459706e-02 1.086589e+00 -2.373529e-02 -2.832217e+01
-2.579624e-08 -1.967350e-09 -1.210182e-06 -4.161774e-09 -8.641286e-06 -6.208313e-08 -1.117334e-05 -3.064790e-05
-9.417563e-03 3.523924e-02 -8.187868e-04 -2.319515e-01 -5.228767e-03 1.896648e-01 2.048313e-03 -1.435757e+01
1.815132e+00 1.200168e-03 6.309525e-02 3.454065e-03 -9.499130e-02 -6.578861e-03 5.878848e-01 -5.296680e+00
[ getOption("max.print") est atteint -- 7 lignes omises ]
Model rank = 7802 / 7802
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00e+00 7.67e+00 1 0.41
s(measurement.no):toneBis.ord1 9.00e+00 3.09e+00 1 0.36
s(measurement.no):toneBis.ord2 9.00e+00 1.00e+00 1 0.43
s(measurement.no):toneBis.ord3 9.00e+00 3.53e+00 1 0.45
s(measurement.no,speaker) 1.00e+02 3.85e+01 1 0.38
s(measurement.no,speaker):toneBis.ord1 1.00e+02 1.64e-02 1 0.44
s(measurement.no,speaker):toneBis.ord2 1.00e+02 1.37e-03 1 0.48
s(measurement.no,speaker):toneBis.ord3 1.00e+02 6.92e-03 1 0.39
s(measurement.no,speakerLeftRightTone) 6.00e+02 1.63e+02 1 0.41
s(measurement.no,speakerLeftRightTone):toneBis.ord1 6.00e+02 3.09e+01 1 0.43
s(measurement.no,speakerLeftRightTone):toneBis.ord2 6.00e+02 1.22e+01 1 0.43
s(measurement.no,speakerLeftRightTone):toneBis.ord3 6.00e+02 1.86e+02 1 0.48
s(measurement.no,speakerPos) 3.00e+02 5.97e+01 1 0.46
s(measurement.no,speakerPos):toneBis.ord1 3.00e+02 4.05e+01 1 0.40
s(measurement.no,speakerPos):toneBis.ord2 3.00e+02 5.66e+01 1 0.43
s(measurement.no,speakerPos):toneBis.ord3 3.00e+02 3.93e+01 1 0.38
s(measurement.no,word) 9.75e+02 1.52e+02 1 0.46
s(measurement.no,wordPos) 1.43e+03 3.31e+02 1 0.42
s(measurement.no,wordLeftRightTone) 1.36e+03 5.31e+02 1 0.50
#Plotting
# Normalized scale
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model1c, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", ylim = c(-1, 1), lwd = 4, xlab = "Time (normalized)", ylab = "F1 (Z)", xaxt = "n", font.lab = 2, hide.label = TRUE)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1c, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"), col = "orange", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1c, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"), col = "chartreuse4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1c, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"), col = "royalblue4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
legend("topright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)# Plotting
# Reconstructed scale
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model1c, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", ylim = c(500, 700), xlab = "Time (ms)", ylab = "F1 (Hz)", xaxt = "n", font.lab = 2, add = F, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT1au * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1au + global_mean1au, hide.label = TRUE)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1c, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"), col = "orange", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT2au * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1au + global_mean1au)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1c, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"), col = "chartreuse4", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT3au * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1au + global_mean1au)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1c, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"), col = "royalblue4", lwd = 4, add = T, transform.view = function(measurement.no) measurement.no * durationT4au * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1au + global_mean1au)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
legend("topright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)# Plotting
# Difference plot between tones
par(mfcol = c(2, 3), mar = c(2, 2, 2, 1), oma = c(4, 4, 2, 1))
plot_diff(gamm.model1c, view="measurement.no", comp=list(toneBis.ord = c("1","2")),rm.ranef=TRUE, main = "1-2", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.000000 - 8.686869
plot_diff(gamm.model1c, view="measurement.no",comp=list(toneBis.ord = c("1","3")),rm.ranef=TRUE, main = "1-3", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.303030 - 10.000000
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
plot_diff(gamm.model1c, view="measurement.no",comp=list(toneBis.ord = c("1","4")),rm.ranef=TRUE, main = "1-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.404040 - 10.000000
plot_diff(gamm.model1c, view="measurement.no",comp=list(toneBis.ord = c("2","3")),rm.ranef=TRUE, main = "2-3", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
3.535354 - 10.000000
plot_diff(gamm.model1c, view="measurement.no",comp=list(toneBis.ord = c("2","4")),rm.ranef=TRUE, main = "2-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
plot_diff(gamm.model1c, view="measurement.no",comp=list(toneBis.ord = c("3","4")),rm.ranef=TRUE, main = "3-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
1.515152 - 10.000000
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
mtext("Difference in F1 (Z)", side = 2, outer = TRUE, line = 2.5, cex = 1.2, font = 2)plot_parametric(gamm.model1c, pred = list(toneBis.ord=c("1", "2", "3", "4")), main = "Tone", xlab = "F1 (Z)")Summary:
* toneBis.ord : factor; set to the value(s): 1, 2, 3, 4.
* measurement.no : numeric predictor; set to the value(s): 5.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
gamm.model1d.noAR <- bam(f1Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.au.fem, method="fREML", discrete = TRUE, nthreads = ncores)# Auto-regressive model
gamm.model1d <- bam(f1Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.au.fem, method="fREML", rho = r.gamm.model1d, AR.start = data.au.fem$start, discrete = TRUE, nthreads = ncores)
Family: gaussian
Link function: identity
Formula:
f1Zscore2 ~ toneBis.ord + s(measurement.no, bs = "cr") + s(measurement.no,
by = toneBis.ord, bs = "cr") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speaker, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = toneBis.ord) + s(measurement.no, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1, by = toneBis.ord) + s(measurement.no, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerPos, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = toneBis.ord) + s(measurement.no, word, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordPos, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 3, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.16219 0.05724 2.834 0.00461 **
toneBis.ord1 -0.35416 0.08495 -4.169 3.09e-05 ***
toneBis.ord2 -0.17573 0.08834 -1.989 0.04671 *
toneBis.ord3 0.06142 0.07753 0.792 0.42827
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 8.099 8.313 111.901 < 2e-16 ***
s(measurement.no):toneBis.ord1 4.538 5.432 3.894 0.00152 **
s(measurement.no):toneBis.ord2 3.468 4.286 3.950 0.00273 **
s(measurement.no):toneBis.ord3 4.246 5.069 2.037 0.07229 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.745 Deviance explained = 78.3%
fREML = 8460.7 Scale est. = 0.24131 n = 10252
Method: fREML Optimizer: perf chol
$grad
[1] -2.263432e-07 -1.976717e-07 -4.406521e-07 1.689388e-07 2.551381e-06 -5.279386e-05 8.773527e-07 -7.287982e-05 -5.097203e-05
[10] -7.403346e-05 6.809239e-07 -6.501874e-05 -9.847376e-06 4.267025e-08 -1.835476e-07 2.827569e-08 -9.938958e-06 -6.767732e-05
[19] 9.200066e-07 -4.559484e-08 -2.151888e-06 6.358038e-08 -1.777578e-07 3.117976e-08 -3.710818e-05 -5.833773e-07 -4.337288e-07
[28] 8.411823e-08 -6.577230e-06 -2.895434e-08 -1.117279e-05 7.061571e-08 -3.450988e-06 -4.460145e-08 2.880854e-04
$hess
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
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[,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18]
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4.826966e-08 5.300989e-02 -1.660778e-08 1.516154e+01 -7.181350e-03 2.059961e-01 -6.485742e-05 2.045591e-02 -2.628778e-08
8.830783e-06 1.048772e-03 -1.339911e-05 -7.181350e-03 1.239728e+01 -1.401804e-03 -6.271258e-02 -2.017129e-03 -9.008563e-06
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1.130280e-05 -1.022922e-03 -1.861709e-06 -6.485742e-05 -6.271258e-02 -1.574907e-02 8.692207e+00 -1.475071e-03 1.533469e-05
1.957801e-07 -1.140626e-02 -3.211166e-08 2.045591e-02 -2.017129e-03 1.516012e-02 -1.475071e-03 6.327256e-01 8.234094e-08
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-1.054305e-08 8.104957e-01 1.824848e-07 3.082562e-01 3.074863e-03 3.464327e-04 3.023401e-05 3.049563e-03 -5.680324e-08
6.048768e-06 -2.728781e-03 7.251506e-05 6.604647e-04 -2.493408e-01 -1.103673e-04 -1.810824e-01 1.044739e-03 3.327389e-07
-2.301120e-08 6.215264e-02 -1.453757e-07 1.510867e+00 4.552609e-04 -5.803870e-02 -1.371764e-03 -1.040800e-01 -6.639354e-09
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3.207942e-07 -1.957709e-04 -1.783666e-06 -2.705693e-03 6.245040e-03 -1.742444e-03 4.578193e-01 -3.077189e-04 2.510749e-06
2.282393e-11 -6.811420e-07 -4.371616e-14 9.850672e-06 -4.268059e-08 1.836178e-07 -2.828188e-08 9.942378e-06 2.054004e-11
2.838289e-05 2.100485e-03 6.311043e-06 2.275647e-04 1.377342e-01 -2.892137e-05 1.241461e-01 2.727595e-04 2.859461e-05
-9.703763e-09 4.422858e-01 -5.698338e-08 4.916871e-02 4.320569e-04 -6.348153e-03 -5.537533e-04 -2.798626e-04 3.312658e-08
3.033710e-06 -6.493487e-04 1.214390e-04 -1.308908e-03 -1.161469e-01 4.329828e-04 -1.067085e-01 -5.521842e-05 4.597474e-06
[,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26] [,27]
2.772011e-03 -3.504490e-05 -3.839964e-02 -1.765703e-04 -1.731150e-03 1.286741e-05 2.264014e-07 1.750026e-05 1.574863e-03
7.646099e-03 -3.015488e-05 1.684916e-02 -8.811565e-05 3.933000e-02 -1.463523e-04 1.977239e-07 -9.473915e-06 3.081301e-03
4.450527e-03 4.414684e-04 1.814193e-02 7.446677e-04 -7.205234e-04 5.967653e-05 4.407712e-07 7.756894e-04 -4.526982e-04
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3.074863e-03 -2.493408e-01 4.552609e-04 -5.669122e-01 -1.353649e-03 6.245040e-03 -4.268059e-08 1.377342e-01 4.320569e-04
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-1.929429e-02 3.533783e+00 -1.414744e-04 -7.177971e-02 -4.116702e-05 -4.998375e-02 4.560778e-08 3.067298e-02 -9.397574e-04
2.078064e-01 -1.414744e-04 1.100136e+01 -5.728799e-02 -6.189906e-02 -1.717053e-03 2.152876e-06 1.411978e-03 1.084166e-01
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[,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35]
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5.155660e-07 2.527288e-04 2.957060e-07 2.029024e-04 1.120360e-06 5.041652e-04 5.001739e-07 -3.366850e-03
3.033710e-06 2.226380e-07 -1.415280e-05 3.086092e-07 -1.911637e-05 6.383422e-07 -1.106117e-05 -1.185934e-04
-6.493487e-04 1.679894e-01 1.351288e-03 1.179851e-02 2.084263e-03 1.927557e-01 3.106268e-03 -7.442323e+00
1.214390e-04 3.980803e-09 -9.799087e-06 -1.120932e-07 -1.869553e-05 -2.645890e-08 -2.936238e-05 -2.848236e-04
-1.308908e-03 1.874124e+00 2.203628e-03 1.446923e+00 5.731671e-03 5.403847e+00 6.559770e-03 -5.168309e+01
-1.161469e-01 -3.672947e-03 1.305758e+00 -3.228798e-03 2.411451e+00 7.205885e-03 3.829019e+00 -2.238870e+01
4.329828e-04 7.811130e-02 -1.716155e-05 1.267694e-01 -1.305139e-03 1.845445e-01 -1.050663e-03 -5.853152e+00
-1.067085e-01 1.559257e-04 -1.803393e-02 -6.338187e-03 3.902090e-01 -1.368173e-02 2.191919e-01 -1.515289e+01
-5.521842e-05 1.256109e-01 1.137014e-03 2.296203e-01 1.185579e-03 4.889840e-01 1.460659e-03 -6.578798e+00
4.597474e-06 -3.991942e-08 -2.941514e-06 -6.237097e-08 -1.745894e-05 -1.349976e-07 5.957818e-06 -1.583714e-04
2.843962e-03 1.582936e-01 6.043350e-04 1.923116e-01 2.027460e-03 3.824882e-01 3.699380e-04 -1.475162e+01
6.433080e-01 1.790135e-03 1.624946e-01 -1.844016e-03 1.867315e-02 4.297133e-03 5.963202e-01 -9.144651e+00
5.181299e-04 2.529623e-01 -1.954315e-03 2.273077e-01 -1.054465e-02 1.289267e+00 -5.948466e-03 -2.824699e+01
-7.124836e-01 -1.118320e-03 -7.321193e-02 -3.539665e-03 -2.010042e-01 -1.280070e-03 -5.106159e-01 -9.528931e+00
-5.553771e-04 3.471603e-02 -1.138120e-04 -6.272792e-02 -1.206359e-03 1.103864e-01 -8.097978e-04 -5.086359e+00
-1.205477e-02 -2.672290e-03 -7.624514e-02 -1.477304e-03 -2.253861e-01 -2.954305e-03 -9.091869e-02 -4.991273e+00
-8.414271e-08 6.579429e-06 2.896277e-08 1.117641e-05 -7.063274e-08 3.452499e-06 4.461275e-08 -2.881613e-04
-9.675473e-02 1.275920e-03 4.701303e-02 -6.415411e-03 5.138981e-01 5.410833e-03 3.255360e-01 -4.452017e+00
2.608824e-03 8.457272e-02 5.461874e-04 8.411937e-02 1.044321e-03 5.224196e-02 8.346469e-04 -6.073009e+00
5.570895e+00 -5.487112e-04 -1.418358e-01 -6.669694e-03 -2.634647e-01 4.374331e-04 -6.774332e-01 -8.751659e+00
[ getOption("max.print") est atteint -- 7 lignes omises ]
Model rank = 7542 / 7542
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00e+00 8.10e+00 1.01 0.84
s(measurement.no):toneBis.ord1 9.00e+00 4.54e+00 1.01 0.82
s(measurement.no):toneBis.ord2 9.00e+00 3.47e+00 1.01 0.80
s(measurement.no):toneBis.ord3 9.00e+00 4.25e+00 1.01 0.84
s(measurement.no,speaker) 1.00e+02 5.06e+01 1.01 0.83
s(measurement.no,speaker):toneBis.ord1 1.00e+02 1.56e+01 1.01 0.83
s(measurement.no,speaker):toneBis.ord2 1.00e+02 7.22e-03 1.01 0.86
s(measurement.no,speaker):toneBis.ord3 1.00e+02 1.49e+01 1.01 0.85
s(measurement.no,speakerLeftRightTone) 5.80e+02 1.48e+02 1.01 0.85
s(measurement.no,speakerLeftRightTone):toneBis.ord1 5.80e+02 4.20e+01 1.01 0.83
s(measurement.no,speakerLeftRightTone):toneBis.ord2 5.80e+02 1.32e+01 1.01 0.89
s(measurement.no,speakerLeftRightTone):toneBis.ord3 5.80e+02 4.78e+01 1.01 0.85
s(measurement.no,speakerPos) 3.00e+02 7.56e+01 1.01 0.82
s(measurement.no,speakerPos):toneBis.ord1 3.00e+02 2.02e+01 1.01 0.86
s(measurement.no,speakerPos):toneBis.ord2 3.00e+02 8.90e+00 1.01 0.85
s(measurement.no,speakerPos):toneBis.ord3 3.00e+02 2.96e+01 1.01 0.81
s(measurement.no,word) 9.30e+02 1.84e+02 1.01 0.84
s(measurement.no,wordPos) 1.39e+03 3.87e+02 1.01 0.89
s(measurement.no,wordLeftRightTone) 1.27e+03 4.42e+02 1.01 0.86
# Plotting
# Normalized scale
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model1d, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"), col = "orange", ylim = c(-1, 1), lwd = 4, xlab = "Time (normalized)", ylab = "F1 (Z)", xaxt = "n", font.lab = 2)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1d, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1d, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"), col = "chartreuse4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1d, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"), col = "royalblue4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
legend("topright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)# Plotting
# Reconstructed scale
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model1d, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"), col = "orange", ylim = c(550, 900), xlab = "Time (ms)", ylab = "F1 (Hz)", xaxt = "n", font.lab = 2, add = F, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT2auf * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1auf + global_mean1auf, hide.label = TRUE)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1d, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT1auf * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1auf + global_mean1auf)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1d, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"), col = "chartreuse4", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT3auf * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1auf + global_mean1auf)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1d, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"), col = "royalblue4", lwd = 4, add = T, transform.view = function(measurement.no) measurement.no * durationT4auf * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1auf + global_mean1auf)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
legend("topright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)# Plotting
# Difference plots between tones
par(mfcol = c(2, 3), mar = c(2, 2, 2, 1), oma = c(4, 4, 2, 1))
plot_diff(gamm.model1d, view="measurement.no", comp=list(toneBis.ord = c("1","2")),rm.ranef=TRUE, main = "1-2", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.606061 - 5.959596
9.191919 - 10.000000
plot_diff(gamm.model1d, view="measurement.no",comp=list(toneBis.ord = c("1","3")),rm.ranef=TRUE, main = "1-3", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.303030 - 8.888889
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
plot_diff(gamm.model1d, view="measurement.no",comp=list(toneBis.ord = c("1","4")),rm.ranef=TRUE, main = "1-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.000000 - 8.181818
plot_diff(gamm.model1d, view="measurement.no",comp=list(toneBis.ord = c("2","3")),rm.ranef=TRUE, main = "2-3", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
6.161616 - 10.000000
plot_diff(gamm.model1d, view="measurement.no",comp=list(toneBis.ord = c("2","4")),rm.ranef=TRUE, main = "2-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
6.666667 - 10.000000
plot_diff(gamm.model1d, view="measurement.no",comp=list(toneBis.ord = c("3","4")),rm.ranef=TRUE, main = "3-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
mtext("Difference in F1 (Z)", side = 2, outer = TRUE, line = 2.5, cex = 1.2, font = 2)plot_parametric(gamm.model1d, pred = list(toneBis.ord=c("1", "2", "3", "4")), xlab = "F1 (Z)", main = "Tone")Summary:
* toneBis.ord : factor; set to the value(s): 1, 2, 3, 4.
* measurement.no : numeric predictor; set to the value(s): 5.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
gamm.initialOrder.noAR <- bam(f1Zscore2 ~ tone.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=tone.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=tone.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=tone.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=tone.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.au.mas, method="fREML", discrete = TRUE, nthreads = ncores)# Auto-regressive model
gamm.InitialOrder <- bam(f1Zscore2 ~ tone.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=tone.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=tone.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=tone.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=tone.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.au.mas, method="fREML", rho = r.gamm.initialOrder, AR.start = data.au.mas$start, discrete = TRUE, nthreads = ncores)
Family: gaussian
Link function: identity
Formula:
f1Zscore2 ~ tone.ord + s(measurement.no, bs = "cr") + s(measurement.no,
by = tone.ord, bs = "cr") + s(measurement.no, speaker, bs = "fs",
xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speaker, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = tone.ord) + s(measurement.no, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1, by = tone.ord) + s(measurement.no, speakerPos, bs = "fs",
xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerPos, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = tone.ord) + s(measurement.no, word, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordPos, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 3, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.42981 0.07043 -6.103 1.08e-09 ***
tone.ord2 0.49433 0.10315 4.792 1.68e-06 ***
tone.ord3 0.79634 0.10038 7.934 2.38e-15 ***
tone.ord4 0.49171 0.08219 5.983 2.27e-09 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 7.629 8.003 40.127 < 2e-16 ***
s(measurement.no):tone.ord2 1.942 2.239 0.992 0.31439
s(measurement.no):tone.ord3 3.698 4.288 4.171 0.00183 **
s(measurement.no):tone.ord4 2.745 3.322 2.009 0.09147 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.655 Deviance explained = 70.7%
fREML = 10549 Scale est. = 0.32538 n = 10857
#Plotting
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.InitialOrder, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(tone.ord = "1"), col = "red", ylim = c(-1, 1), lwd = 4, xlab = "Time (normalized)", ylab = "F1 (Z)", xaxt = "n", font.lab = 2)Summary:
* tone.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):tone.ord2,s(measurement.no,speaker):tone.ord3,s(measurement.no,speaker):tone.ord4,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):tone.ord2,s(measurement.no,speakerLeftRightTone):tone.ord3,s(measurement.no,speakerLeftRightTone):tone.ord4,s(measurement.no,speakerPos),s(measurement.no,speakerPos):tone.ord2,s(measurement.no,speakerPos):tone.ord3,s(measurement.no,speakerPos):tone.ord4,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.InitialOrder, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(tone.ord = "2"), col = "orange", add = T, lwd = 4)Summary:
* tone.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):tone.ord2,s(measurement.no,speaker):tone.ord3,s(measurement.no,speaker):tone.ord4,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):tone.ord2,s(measurement.no,speakerLeftRightTone):tone.ord3,s(measurement.no,speakerLeftRightTone):tone.ord4,s(measurement.no,speakerPos),s(measurement.no,speakerPos):tone.ord2,s(measurement.no,speakerPos):tone.ord3,s(measurement.no,speakerPos):tone.ord4,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.InitialOrder, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(tone.ord = "3"), col = "chartreuse4", add = T, lwd = 4)Summary:
* tone.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):tone.ord2,s(measurement.no,speaker):tone.ord3,s(measurement.no,speaker):tone.ord4,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):tone.ord2,s(measurement.no,speakerLeftRightTone):tone.ord3,s(measurement.no,speakerLeftRightTone):tone.ord4,s(measurement.no,speakerPos),s(measurement.no,speakerPos):tone.ord2,s(measurement.no,speakerPos):tone.ord3,s(measurement.no,speakerPos):tone.ord4,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.InitialOrder, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(tone.ord = "4"), col = "royalblue4", add = T, lwd = 4)Summary:
* tone.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):tone.ord2,s(measurement.no,speaker):tone.ord3,s(measurement.no,speaker):tone.ord4,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):tone.ord2,s(measurement.no,speakerLeftRightTone):tone.ord3,s(measurement.no,speakerLeftRightTone):tone.ord4,s(measurement.no,speakerPos),s(measurement.no,speakerPos):tone.ord2,s(measurement.no,speakerPos):tone.ord3,s(measurement.no,speakerPos):tone.ord4,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
legend("topright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
gamm.model1e.noAR <- bam(f2Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.ai.mas, method="fREML", discrete = TRUE, nthreads = ncores)# Auto-regressive model
gamm.model1e <- bam(f2Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.ai.mas, method="fREML", rho = r.gamm.model1e, AR.start = data.ai.mas$start, discrete = TRUE, nthreads = ncores)
Family: gaussian
Link function: identity
Formula:
f2Zscore2 ~ toneBis.ord + s(measurement.no, bs = "cr") + s(measurement.no,
by = toneBis.ord, bs = "cr") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speaker, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = toneBis.ord) + s(measurement.no, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1, by = toneBis.ord) + s(measurement.no, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerPos, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = toneBis.ord) + s(measurement.no, word, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordPos, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 3, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.01529 0.07512 0.204 0.839
toneBis.ord.L -0.14756 0.10703 -1.379 0.168
toneBis.ord.Q -0.12943 0.13070 -0.990 0.322
toneBis.ord.C 0.21326 0.15164 1.406 0.160
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 5.834 6.242 31.952 < 2e-16 ***
s(measurement.no):toneBis.ord1 3.602 4.282 2.215 0.06010 .
s(measurement.no):toneBis.ord2 3.974 4.973 3.730 0.00268 **
s(measurement.no):toneBis.ord3 3.817 4.801 5.479 9.16e-05 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.644 Deviance explained = 67.8%
fREML = 7619.6 Scale est. = 0.2496 n = 12023
Method: fREML Optimizer: perf chol
$grad
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[10] -3.952394e-14 -1.332268e-15 -4.180206e-05 1.776357e-14 -7.460699e-14 1.278977e-13 -5.773160e-15 3.819167e-14 6.217249e-14
[19] 1.003642e-13 -6.572520e-14 2.060574e-13 1.509903e-13 5.506706e-14 9.769963e-15 -2.398082e-14 1.332268e-14 -5.679150e-05
[28] -3.996803e-15 -2.415845e-13 -1.421085e-14 7.105427e-15 8.526513e-14 -6.394885e-14 -2.486900e-13 -1.000444e-11
$hess
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[,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26] [,27]
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-1.034248e-03 -3.393346e-03 1.217942e-02 -1.232550e-03 1.666439e-02 -4.616135e-03 9.570525e-03 -2.842589e+00
2.346838e-03 -4.421501e-03 5.259171e-04 1.972192e-02 -4.236840e-04 1.035805e-01 2.790196e-05 -1.666341e+00
1.229876e-05 8.627996e-07 3.494815e-06 -4.955435e-08 -6.269002e-06 1.162362e-07 -1.704904e-05 -1.400779e-04
-1.080354e-03 8.523022e-01 -5.418694e-03 1.200342e-01 -6.531862e-05 3.210475e-01 -1.331550e-02 -2.401139e+01
-1.755329e-02 -1.614168e-02 5.749038e-02 -2.735649e-03 9.304945e-02 -3.542529e-02 8.668604e-01 -1.717365e+01
-7.496239e-04 5.871420e-03 -1.236314e-03 1.476181e-01 4.579091e-02 2.388808e-01 -2.330675e-02 -3.321135e+01
-5.288512e-03 -5.736584e-03 6.308972e-02 6.577524e-04 1.576013e-02 -2.292191e-04 -6.249886e-03 -3.112460e+00
1.223291e-04 9.500309e-02 1.633004e-03 6.021000e-02 -8.854823e-04 9.916253e-02 -2.375200e-03 -5.802650e+00
4.510787e-03 -4.914047e-03 -2.821604e-01 -9.518177e-03 -8.187934e-01 -1.856565e-03 -1.124877e+00 -1.359522e+01
3.630302e-03 1.137339e-01 9.762798e-04 1.360212e-02 -2.260512e-03 3.031421e-01 -1.426618e-03 -6.022106e+00
3.406304e-01 6.118956e-02 -3.366006e-01 1.060161e-02 -4.538047e-01 2.528679e-02 -6.929985e-01 -1.018046e+01
-5.064643e-04 1.214331e-01 4.790491e-03 -2.586071e-01 -1.231978e-03 -7.157577e-01 8.633410e-03 -2.436597e+01
-1.443359e-01 -4.120117e-03 -7.048702e-02 -6.091438e-04 -3.171609e-01 -1.716519e-03 -1.016692e-01 -9.056666e+00
-6.578235e-04 -2.717570e-01 1.525364e-03 4.896323e-02 1.010079e-02 -1.173263e-01 3.172594e-03 -1.386230e+01
-1.406511e-02 -6.206100e-03 -1.257657e-01 7.147744e-05 -6.704679e-02 -1.175774e-03 -1.037371e-01 -4.799202e+00
1.661884e-04 2.759373e-02 1.207553e-03 2.756418e-02 -1.943155e-03 1.819321e-02 1.061517e-03 -2.147538e+00
6.426981e-03 -6.183219e-03 -1.474789e-01 2.449890e-04 -1.942918e-01 4.109374e-03 -6.494298e-02 -3.323144e+00
-7.383096e-07 5.122037e-06 -3.211159e-08 1.329951e-06 2.572285e-07 1.021388e-05 -8.907799e-08 -2.631901e-04
6.310079e-01 -6.257743e-03 3.958461e-02 -5.718670e-03 2.328244e-01 2.149611e-03 -2.959794e-02 -2.485607e+00
[ getOption("max.print") est atteint -- 7 lignes omises ]
Model rank = 6565 / 6565
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00e+00 5.83e+00 0.99 0.19
s(measurement.no):toneBis.ord1 9.00e+00 3.60e+00 0.99 0.23
s(measurement.no):toneBis.ord2 9.00e+00 3.97e+00 0.99 0.17
s(measurement.no):toneBis.ord3 9.00e+00 3.82e+00 0.99 0.21
s(measurement.no,speaker) 1.00e+02 5.47e+01 0.99 0.24
s(measurement.no,speaker):toneBis.ord1 1.00e+02 4.54e-03 0.99 0.21
s(measurement.no,speaker):toneBis.ord2 1.00e+02 1.23e+01 0.99 0.20
s(measurement.no,speaker):toneBis.ord3 1.00e+02 3.33e+00 0.99 0.23
s(measurement.no,speakerLeftRightTone) 5.90e+02 8.24e+01 0.99 0.18
s(measurement.no,speakerLeftRightTone):toneBis.ord1 5.90e+02 7.26e+01 0.99 0.24
s(measurement.no,speakerLeftRightTone):toneBis.ord2 5.90e+02 3.88e+01 0.99 0.17
s(measurement.no,speakerLeftRightTone):toneBis.ord3 5.90e+02 3.24e+01 0.99 0.23
s(measurement.no,speakerPos) 3.00e+02 6.68e+01 0.99 0.17
s(measurement.no,speakerPos):toneBis.ord1 3.00e+02 3.73e+01 0.99 0.20
s(measurement.no,speakerPos):toneBis.ord2 3.00e+02 1.09e+01 0.99 0.20
s(measurement.no,speakerPos):toneBis.ord3 3.00e+02 4.97e+00 0.99 0.21
s(measurement.no,word) 6.30e+02 3.10e+02 0.99 0.25
s(measurement.no,wordPos) 9.99e+02 1.70e+02 0.99 0.23
s(measurement.no,wordLeftRightTone) 9.36e+02 2.27e+02 0.99 0.18
# Plotting
# Normalized scale
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model1e, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", ylim = c(-1, 1), lwd = 4, xlab = "Time (normalized)", ylab = "F2 (Z)", xaxt = "n", font.lab = 2)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1e, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"), col = "orange", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1e, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"), col = "chartreuse4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1e, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"), col = "royalblue4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
legend("topright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)# Plotting
# Reconstructed scale
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model1e, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", ylim = c(1400, 1800), xlab = "Time (ms)", ylab = "F2 (Hz)", xaxt = "n", font.lab = 2, add = F, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT1 * 0.1, transform = function(f2Zscore2) f2Zscore2 * global_sd2 + global_mean2, hide.label = TRUE)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1e, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"), col = "orange", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT2 * 0.1, transform = function(f2Zscore2) f2Zscore2 * global_sd2 + global_mean2)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1e, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"), col = "chartreuse4", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT3 * 0.1, transform = function(f2Zscore2) f2Zscore2 * global_sd2 + global_mean2)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1e, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"), col = "royalblue4", lwd = 4, add = T, transform.view = function(measurement.no) measurement.no * durationT4 * 0.1, transform = function(f2Zscore2) f2Zscore2 * global_sd2 + global_mean2)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
legend("bottomright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)# Plotting
# Difference plot between tones
par(mfcol = c(2, 3), mar = c(2, 2, 2, 1), oma = c(4, 4, 2, 1))
plot_diff(gamm.model1e, view="measurement.no", comp=list(toneBis.ord = c("1","2")),rm.ranef=TRUE, main = "1-2", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.000000 - 2.020202
plot_diff(gamm.model1e, view="measurement.no",comp=list(toneBis.ord = c("1","3")),rm.ranef=TRUE, main = "1-3", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.000000 - 1.717172
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
plot_diff(gamm.model1e, view="measurement.no",comp=list(toneBis.ord = c("1","4")),rm.ranef=TRUE, main = "1-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
plot_diff(gamm.model1e, view="measurement.no",comp=list(toneBis.ord = c("2","3")),rm.ranef=TRUE, main = "2-3", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
plot_diff(gamm.model1e, view="measurement.no",comp=list(toneBis.ord = c("2","4")),rm.ranef=TRUE, main = "2-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.000000 - 1.919192
plot_diff(gamm.model1e, view="measurement.no",comp=list(toneBis.ord = c("3","4")),rm.ranef=TRUE, main = "3-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.000000 - 1.414141
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
mtext("Difference in F2 (Z)", side = 2, outer = TRUE, line = 2.5, cex = 1.2, font = 2)plot_parametric(gamm.model1e, pred = list(toneBis.ord=c("1", "2", "3", "4")), xlab = "F2 (Z)", main = "Tone")Summary:
* toneBis.ord : factor; set to the value(s): 1, 2, 3, 4.
* measurement.no : numeric predictor; set to the value(s): 5.
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
gamm.model1f.noAR <- bam(f2Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.ai.fem, method="fREML", discrete = TRUE, nthreads = ncores)# Auto-regressive model
gamm.model1f <- bam(f2Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.ai.fem, method="fREML", rho = r.gamm.model1f, AR.start = data.ai.fem$start, discrete = TRUE, nthreads = ncores)
Family: gaussian
Link function: identity
Formula:
f2Zscore2 ~ toneBis.ord + s(measurement.no, bs = "cr") + s(measurement.no,
by = toneBis.ord, bs = "cr") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speaker, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = toneBis.ord) + s(measurement.no, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1, by = toneBis.ord) + s(measurement.no, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerPos, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = toneBis.ord) + s(measurement.no, word, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordPos, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 3, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.01759 0.06436 0.273 0.785
toneBis.ord1 -0.10687 0.24338 -0.439 0.661
toneBis.ord2 0.07739 0.12629 0.613 0.540
toneBis.ord3 -0.02991 0.16311 -0.183 0.854
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 2.993 3.301 8.992 3.41e-06 ***
s(measurement.no):toneBis.ord1 1.698 1.920 1.032 0.2849
s(measurement.no):toneBis.ord2 1.000 1.001 3.952 0.0468 *
s(measurement.no):toneBis.ord3 1.262 1.360 1.279 0.2068
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.469 Deviance explained = 51.9%
fREML = 10968 Scale est. = 0.45463 n = 11198
Method: fREML Optimizer: perf chol
$grad
[1] -8.680216e-09 -3.818379e-08 -3.832142e-05 -2.706223e-07 2.075530e-06 -4.120451e-09 -5.147328e-05 -4.062929e-05 -4.213564e-05
[10] -1.307415e-08 -3.909493e-05 1.569795e-07 -4.827928e-06 1.250390e-07 -2.757438e-08 -2.751360e-08 -1.294878e-08 5.329621e-08
[19] -4.373979e-05 -3.576229e-07 -3.297578e-07 5.353744e-10 -7.308002e-08 -1.399523e-08 -2.017717e-08 -3.045525e-09 -8.080303e-07
[28] 1.043800e-07 -2.594111e-06 -1.904703e-07 -1.472385e-05 5.402271e-07 -2.314541e-06 -2.590902e-07 2.108991e-04
$hess
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
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-1.930705e-02 1.520758e-01 -6.195473e-06 3.091282e-03 7.003164e-04 -4.871926e-04 3.531726e-07 4.822612e-09 -1.757666e-07
-3.226213e-05 -6.195473e-06 3.833632e-05 4.997395e-06 5.900655e-06 -7.992972e-08 -6.589872e-11 2.940762e-13 6.031342e-10
8.397579e-03 3.091282e-03 4.997395e-06 1.477972e-02 -1.743697e-02 1.406031e-04 2.625273e-08 1.728462e-09 1.631168e-07
3.502305e-01 7.003164e-04 5.900655e-06 -1.743697e-02 1.860259e+01 3.349125e-02 2.994159e-06 2.667247e-07 2.023175e-05
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-3.039013e-07 3.531726e-07 -6.589872e-11 2.625273e-08 2.994159e-06 -2.402172e-08 5.147416e-05 5.204887e-13 -9.187162e-12
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-1.109815e-06 -1.757666e-07 6.031342e-10 1.631168e-07 2.023175e-05 -8.595425e-08 -9.187162e-12 6.404318e-13 4.213742e-05
2.165835e-05 3.484902e-05 -2.463351e-07 1.945314e-04 2.555953e-03 -4.144252e-02 2.336192e-09 -1.868238e-08 -7.766648e-07
2.321810e-02 9.882114e-03 6.855199e-06 4.347112e-02 -5.462106e-01 -2.605900e-05 3.524206e-07 -1.833161e-08 1.799308e-06
-1.617145e-04 -1.543894e-04 -3.595463e-08 -4.685308e-04 9.308661e-07 -3.650114e-02 -5.786495e-10 -4.171554e-07 3.279861e-08
1.646267e-02 3.734402e-03 4.332693e-06 -4.723268e-04 7.219024e-01 9.611287e-04 1.184157e-06 1.596543e-08 -9.358312e-08
3.393494e-04 -7.691454e-04 6.592938e-08 2.845870e-04 4.839794e-02 3.149861e-01 -3.388703e-08 1.019625e-06 -4.013356e-08
-2.752228e-03 7.911465e-03 -6.700675e-07 2.698351e-04 2.883183e-02 -1.590480e-04 6.650317e-06 -1.218173e-07 -1.422349e-07
2.302906e-05 -1.069552e-04 -1.736894e-08 4.606923e-05 1.415211e-03 -1.258425e-02 9.769980e-08 -2.199708e-06 7.523372e-09
-5.445899e-03 -1.462877e-03 5.236577e-06 -7.837374e-05 9.707050e-02 3.413423e-04 -1.584488e-07 3.951092e-09 6.409136e-06
4.630002e-04 2.028613e-04 1.057648e-07 -2.348404e-04 -1.082255e-02 -2.751171e-02 3.961053e-09 -8.798374e-08 -2.259283e-07
8.681042e-09 3.818900e-08 8.116081e-11 2.706613e-07 -2.075839e-06 4.120654e-09 3.189484e-12 1.324348e-13 -1.499435e-11
-4.795063e-05 -1.191310e-05 8.050279e-08 -7.326568e-05 -2.711915e-03 -5.484909e-03 4.460416e-09 2.861714e-09 3.504736e-09
1.607131e-02 -1.545276e-03 7.384527e-07 -2.901245e-03 1.083799e+00 2.306361e-03 -1.522510e-07 2.382708e-08 3.401256e-06
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-7.070520e-03 -1.624012e-02 -2.660129e-06 1.206649e-03 2.547314e-01 -1.610947e-03 5.395028e-05 3.727995e-07 -6.899120e-07
-2.325632e-04 1.614707e-03 2.176382e-08 9.042713e-05 4.385212e-03 -1.488950e-02 1.281461e-07 -1.535037e-06 3.014524e-08
-1.359850e-02 -3.804345e-03 1.142487e-05 4.752608e-03 3.439529e-01 -8.074640e-04 -2.795746e-07 1.736802e-08 2.952453e-05
-5.751961e-05 1.297463e-05 -4.042180e-07 2.297452e-04 -1.115517e-03 -2.266220e-02 -1.965011e-09 -2.391081e-07 -2.670192e-07
4.605224e-04 1.321624e-04 4.877003e-08 5.598466e-04 -2.588102e-03 1.596977e-05 4.000689e-09 6.003146e-10 8.981157e-08
-9.803994e-05 -3.677274e-05 -5.865504e-08 -1.081200e-04 -1.143095e-03 -1.700310e-02 -1.658247e-09 -1.941430e-07 -1.955776e-08
[,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18]
2.165835e-05 2.321810e-02 -1.617145e-04 1.646267e-02 3.393494e-04 -2.752228e-03 2.302906e-05 -5.445899e-03 4.630002e-04
3.484902e-05 9.882114e-03 -1.543894e-04 3.734402e-03 -7.691454e-04 7.911465e-03 -1.069552e-04 -1.462877e-03 2.028613e-04
-2.463351e-07 6.855199e-06 -3.595463e-08 4.332693e-06 6.592938e-08 -6.700675e-07 -1.736894e-08 5.236577e-06 1.057648e-07
1.945314e-04 4.347112e-02 -4.685308e-04 -4.723268e-04 2.845870e-04 2.698351e-04 4.606923e-05 -7.837374e-05 -2.348404e-04
2.555953e-03 -5.462106e-01 9.308661e-07 7.219024e-01 4.839794e-02 2.883183e-02 1.415211e-03 9.707050e-02 -1.082255e-02
-4.144252e-02 -2.605900e-05 -3.650114e-02 9.611287e-04 3.149861e-01 -1.590480e-04 -1.258425e-02 3.413423e-04 -2.751171e-02
2.336192e-09 3.524206e-07 -5.786495e-10 1.184157e-06 -3.388703e-08 6.650317e-06 9.769980e-08 -1.584488e-07 3.961053e-09
-1.868238e-08 -1.833161e-08 -4.171554e-07 1.596543e-08 1.019625e-06 -1.218173e-07 -2.199708e-06 3.951092e-09 -8.798374e-08
-7.766648e-07 1.799308e-06 3.279861e-08 -9.358312e-08 -4.013356e-08 -1.422349e-07 7.523372e-09 6.409136e-06 -2.259283e-07
9.569397e-01 3.284336e-04 -1.491467e-02 7.817115e-04 -5.723585e-03 4.667344e-05 -2.432069e-03 -3.297880e-03 3.681986e-01
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2.748291e-04 5.797480e-03 1.379381e-04 9.859597e-02 2.057709e-03 7.779636e-01 1.846493e-03 -9.492715e-03 1.023744e-03
5.747295e-05 -6.968471e-04 -1.005144e-02 1.908172e-03 4.606862e-02 -4.819446e-03 1.629859e-01 2.717590e-04 -1.016687e-04
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3.058719e-01 1.314776e-03 -1.231566e-02 -1.377482e-03 -1.364549e-01 -6.217936e-06 -3.439337e-03 -2.515359e-03 4.955732e-02
-7.205593e-06 9.115598e-02 1.198224e-05 5.523629e-03 -1.980450e-04 4.086530e-06 8.968962e-06 1.173718e-03 -1.707707e-04
1.631130e-03 -1.706391e-02 5.107935e-01 -1.918595e-03 2.283547e-03 9.244644e-05 2.655193e-03 -2.547562e-04 2.955204e-02
[,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26] [,27]
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2.751715e-08 2.632136e-02 3.624428e-04 -6.882789e-02 1.846493e-03 1.629859e-01 2.372833e-04 -3.439337e-03 8.968962e-06
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2.016450e-08 4.528766e-04 5.028011e-01 1.991545e-03 -2.234707e-02 1.783457e-04 3.292450e+00 -4.184621e-02 6.752231e-03
3.046670e-09 -1.325350e-02 -5.296312e-03 -1.935478e-01 2.307943e-03 -1.001350e-02 -4.184621e-02 2.467040e+00 1.432436e-04
8.081566e-07 -4.657195e-04 1.441468e-03 -8.062306e-05 -2.184207e-05 2.182243e-05 6.752231e-03 1.432436e-04 9.515830e-03
-1.043987e-07 1.037198e-01 -3.727596e-03 -5.587930e-02 5.552556e-04 -8.557728e-03 -3.201470e-05 1.201616e-02 1.910125e-04
[,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35]
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1.631130e-03 -3.313858e-03 -2.050332e-01 -7.525615e-04 -1.239484e-01 2.250413e-03 -8.866007e-02 -2.060179e+00
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5.107935e-01 1.048434e-02 -1.044820e-01 3.240730e-03 -4.986571e-02 2.328300e-03 -4.790406e-02 -2.313245e+00
-1.918595e-03 -1.566408e-01 -6.806189e-03 4.001113e-02 -8.458014e-03 3.329030e-02 -8.507843e-03 -1.455140e+01
2.283547e-03 -1.291251e-02 -3.642201e-02 -2.424088e-03 7.826512e-02 -1.000503e-02 -6.166251e-01 -1.481612e+01
9.244644e-05 2.332050e-02 -2.733424e-03 3.963072e-02 1.159562e-03 -4.736459e-02 2.169779e-03 -6.155394e+00
2.655193e-03 -2.738249e-02 -1.557734e-02 -1.377524e-02 9.622281e-02 -1.082357e-02 -1.048492e-01 -5.121165e+00
-2.547562e-04 6.985141e-02 -8.414637e-04 1.849721e-02 1.911055e-03 1.819945e-01 1.168761e-03 -6.559820e+00
2.955204e-02 -1.490551e-02 1.263609e-01 -1.007583e-02 1.283007e-01 -2.835415e-02 -2.762107e-02 -1.055743e+01
-1.043987e-07 2.594697e-06 1.905009e-07 1.472650e-05 -5.403156e-07 2.315052e-06 2.591308e-07 -2.109292e-04
1.037198e-01 9.852282e-04 -3.698872e-01 -3.919506e-03 6.721700e-02 4.378847e-03 -8.939731e-02 -2.829340e+00
-3.727596e-03 3.828670e-01 -2.649899e-04 1.974183e-01 -1.426923e-03 1.112492e-01 3.462102e-03 -1.197483e+01
-5.587930e-02 -9.202884e-04 -1.680494e-01 -9.393852e-03 -7.746791e-02 5.855954e-03 -9.722956e-02 -5.848163e+00
5.552556e-04 -1.777997e-01 -1.259961e-03 5.495508e-02 -6.984099e-03 1.789517e-01 9.278401e-04 -4.013049e+01
-8.557728e-03 -5.683042e-05 -3.781561e-02 1.895281e-03 1.577835e-01 -3.637657e-03 -1.105895e-02 -5.261157e+00
-3.201470e-05 -5.429765e-02 1.224458e-03 3.876620e-01 8.853239e-03 2.208250e-01 7.029536e-03 -1.467221e+01
1.201616e-02 -2.774000e-03 -2.155534e-01 5.910518e-03 -1.760124e-01 7.430681e-04 1.183353e-01 -5.101052e+00
1.910125e-04 -1.547499e-02 -2.477674e-04 3.447358e-03 2.446402e-04 -3.410851e-04 1.363043e-04 -6.138985e-01
1.692993e+00 1.338352e-02 5.249003e-02 -1.413601e-02 1.360782e-01 5.228264e-03 -1.091880e-01 -4.476002e+00
[ getOption("max.print") est atteint -- 7 lignes omises ]
Model rank = 6427 / 6427
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00e+00 2.99e+00 1 0.47
s(measurement.no):toneBis.ord1 9.00e+00 1.70e+00 1 0.51
s(measurement.no):toneBis.ord2 9.00e+00 1.00e+00 1 0.53
s(measurement.no):toneBis.ord3 9.00e+00 1.26e+00 1 0.47
s(measurement.no,speaker) 1.00e+02 5.50e+01 1 0.46
s(measurement.no,speaker):toneBis.ord1 1.00e+02 6.84e-04 1 0.43
s(measurement.no,speaker):toneBis.ord2 1.00e+02 4.12e+00 1 0.41
s(measurement.no,speaker):toneBis.ord3 1.00e+02 3.83e+01 1 0.46
s(measurement.no,speakerLeftRightTone) 5.90e+02 5.87e+01 1 0.48
s(measurement.no,speakerLeftRightTone):toneBis.ord1 5.90e+02 2.26e+01 1 0.53
s(measurement.no,speakerLeftRightTone):toneBis.ord2 5.90e+02 3.42e+01 1 0.46
s(measurement.no,speakerLeftRightTone):toneBis.ord3 5.90e+02 5.66e+00 1 0.43
s(measurement.no,speakerPos) 3.00e+02 3.56e+01 1 0.48
s(measurement.no,speakerPos):toneBis.ord1 3.00e+02 9.08e+01 1 0.36
s(measurement.no,speakerPos):toneBis.ord2 3.00e+02 3.95e+01 1 0.45
s(measurement.no,speakerPos):toneBis.ord3 3.00e+02 1.02e+01 1 0.46
s(measurement.no,word) 6.15e+02 2.60e+02 1 0.45
s(measurement.no,wordPos) 9.33e+02 1.99e+02 1 0.46
s(measurement.no,wordLeftRightTone) 8.79e+02 1.90e+02 1 0.42
# Plotting
# Normalized scale
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model1f, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", ylim = c(-1, 1), lwd = 4, xlab = "Time (normalized)", ylab = "F2 (Z)", xaxt = "n", font.lab = 2)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1f, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"), col = "orange", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1f, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"), col = "chartreuse4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1f, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"), col = "royalblue4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
legend("topright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)# Plotting
# Reconstructed scale
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model1f, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"), col = "orange", ylim = c(1700, 2050), xlab = "Time (ms)", ylab = "F2 (Hz)", xaxt = "n", font.lab = 2, add = F, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT2f * 0.1, transform = function(f2Zscore2) f2Zscore2 * global_sd2f + global_mean2f, hide.label = TRUE)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1f, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"), col = "royalblue4", lwd = 4, add = T, transform.view = function(measurement.no) measurement.no * durationT4f * 0.1, transform = function(f2Zscore2) f2Zscore2 * global_sd2f + global_mean2f)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1f, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT1f * 0.1, transform = function(f2Zscore2) f2Zscore2 * global_sd2f + global_mean2f)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1f, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"), col = "chartreuse4", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT3f * 0.1, transform = function(f2Zscore2) f2Zscore2 * global_sd2f + global_mean2f)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
legend("bottomright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)# Plotting
# Difference plot between tones
par(mfcol = c(2, 3), mar = c(2, 2, 2, 1), oma = c(4, 4, 2, 1))
plot_diff(gamm.model1f, view="measurement.no", comp=list(toneBis.ord = c("1","2")),rm.ranef=TRUE, main = "1-2", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
plot_diff(gamm.model1f, view="measurement.no",comp=list(toneBis.ord = c("1","3")),rm.ranef=TRUE, main = "1-3", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
plot_diff(gamm.model1f, view="measurement.no",comp=list(toneBis.ord = c("1","4")),rm.ranef=TRUE, main = "1-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
plot_diff(gamm.model1f, view="measurement.no",comp=list(toneBis.ord = c("2","3")),rm.ranef=TRUE, main = "2-3", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
plot_diff(gamm.model1f, view="measurement.no",comp=list(toneBis.ord = c("2","4")),rm.ranef=TRUE, main = "2-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
plot_diff(gamm.model1f, view="measurement.no",comp=list(toneBis.ord = c("3","4")),rm.ranef=TRUE, main = "3-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
mtext("Difference in F2 (Z)", side = 2, outer = TRUE, line = 2.5, cex = 1.2, font = 2)plot_parametric(gamm.model1f, pred = list(toneBis.ord=c("1", "2", "3", "4")), xlab = "F2 (Z)", main = "Tone")Summary:
* toneBis.ord : factor; set to the value(s): 1, 2, 3, 4.
* measurement.no : numeric predictor; set to the value(s): 5.
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
gamm.model1g.noAR <- bam(f2Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.au.mas, method="fREML", discrete = TRUE, nthreads = ncores)# Auto-regressive model
gamm.model1g <- bam(f2Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.au.mas, method="fREML", rho = r.gamm.model1g, AR.start = data.au.mas$start, discrete = TRUE, nthreads = ncores)
Family: gaussian
Link function: identity
Formula:
f2Zscore2 ~ toneBis.ord + s(measurement.no, bs = "cr") + s(measurement.no,
by = toneBis.ord, bs = "cr") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speaker, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = toneBis.ord) + s(measurement.no, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1, by = toneBis.ord) + s(measurement.no, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerPos, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = toneBis.ord) + s(measurement.no, word, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordPos, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 3, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.04924 0.06351 0.775 0.4381
toneBis.ord1 -0.19064 0.10813 -1.763 0.0779 .
toneBis.ord2 -0.19199 0.16524 -1.162 0.2453
toneBis.ord3 -0.09237 0.13347 -0.692 0.4889
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 7.165 7.777 54.388 <2e-16 ***
s(measurement.no):toneBis.ord1 1.616 1.831 0.119 0.854
s(measurement.no):toneBis.ord2 1.698 1.966 0.519 0.593
s(measurement.no):toneBis.ord3 2.001 2.377 1.142 0.274
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.726 Deviance explained = 77%
fREML = 9170.2 Scale est. = 0.24868 n = 10857
Method: fREML Optimizer: perf chol
$grad
[1] 2.229328e-13 -1.039169e-13 -1.226241e-13 4.013456e-13 -5.329071e-15 -2.220446e-14 9.592327e-14 1.310063e-14 -4.903654e-05
[10] -7.888230e-05 -9.703349e-14 7.105427e-14 -3.197442e-13 1.207923e-13 -1.350031e-13 2.486900e-13 -5.989232e-05 -7.860379e-14
[19] -9.947598e-14 3.019807e-14 3.197442e-14 -4.796163e-14 -6.579657e-05 -5.042393e-05 1.030287e-13 4.618528e-14 5.329071e-14
[28] 1.394440e-13 -3.126388e-13 -1.008971e-12 1.421085e-13 4.689582e-13 -5.684342e-14 7.105427e-13 9.094947e-12
$hess
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
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2.316266e-02 3.980832e-02 -1.062052e-02 2.157234e-02 -2.195134e-03 -4.651760e-05 4.614615e-02 1.518743e-04 1.627740e-08
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-5.515869e-02 2.157234e-02 4.053160e-02 2.885601e-01 -4.320236e-03 1.940318e-04 3.109130e-03 5.644838e-05 1.365900e-07
-6.066135e-02 -2.195134e-03 -1.583566e-02 -4.320236e-03 2.412681e+00 6.689216e-03 -1.198989e-02 9.770154e-04 9.245564e-07
4.707938e-06 -4.651760e-05 4.027810e-05 1.940318e-04 6.689216e-03 1.311127e+00 1.126068e-04 -1.140562e-01 9.501505e-09
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-1.806840e-02 4.151006e-03 -1.477690e-03 2.640669e-02 9.901812e-02 1.390322e-03 2.649766e-02 4.105578e-05 1.051161e-06
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[,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18]
-7.305871e-10 -8.451302e-04 -3.168470e-05 6.200292e-03 -6.926706e-05 1.726737e-02 3.764560e-05 3.076055e-08 -3.894257e-05
7.964168e-10 2.044229e-04 8.746443e-06 1.317073e-02 -2.536088e-04 6.078346e-02 2.628084e-04 -1.095645e-07 2.687697e-05
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-4.947116e-06 3.217867e-05 -4.396729e-02 4.031927e-03 7.862587e-01 -1.133598e-03 -1.659597e-01 1.335006e-08 -3.718060e-02
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-1.458317e-06 -6.702921e-06 -2.052291e-03 -6.283709e-04 -4.769456e-02 6.964696e-03 5.094348e-01 -1.006685e-08 -1.553169e-02
2.026651e-11 1.758484e-08 -2.847634e-09 3.211098e-07 2.947175e-09 -6.915297e-07 -6.350002e-10 3.523436e-10 1.200411e-07
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-2.050451e-08 -1.194758e-02 3.366967e-04 1.226825e+01 7.700868e-02 7.738119e-01 3.013264e-03 8.265483e-07 4.617527e-04
2.965460e-06 3.281816e-05 -5.496669e-02 7.700868e-02 1.048073e+01 1.038945e-02 -2.970130e-03 1.024402e-08 -1.257342e-01
-1.557946e-08 1.373393e-04 -3.100722e-05 7.738119e-01 1.038945e-02 1.201541e+01 5.469194e-02 -1.685569e-06 -8.880102e-05
-1.421767e-07 9.778121e-06 1.454865e-02 3.013264e-03 -2.970130e-03 5.469194e-02 4.042026e+00 4.713961e-09 -1.747234e-02
4.716587e-11 8.854692e-08 -6.256216e-09 8.265483e-07 1.024402e-08 -1.685569e-06 4.713961e-09 5.989440e-05 6.459432e-07
4.348406e-05 -1.156317e-06 4.271824e-03 4.617527e-04 -1.257342e-01 -8.880102e-05 -1.747234e-02 6.459432e-07 1.787920e+00
7.689642e-08 6.150664e-02 2.798424e-03 -3.992483e-01 -1.138000e-03 6.289388e-02 7.489288e-04 8.302777e-07 8.224739e-05
-8.815555e-06 2.459809e-04 3.223812e-01 3.147687e-03 -3.882249e-01 -9.079899e-04 9.669501e-03 7.707207e-08 -1.794346e-02
-4.457709e-08 -2.089977e-04 -2.569032e-04 6.422756e-01 3.763017e-03 4.368643e-01 2.627193e-03 4.379773e-06 -3.161759e-04
1.087427e-06 -1.232699e-05 3.093683e-02 7.003735e-04 3.476545e-01 -2.551545e-03 -1.757162e-01 4.317841e-09 -5.963117e-03
-7.880084e-13 2.600275e-08 -7.652363e-09 -3.768505e-06 3.490936e-07 1.057619e-04 8.334761e-07 -1.452046e-11 -2.574785e-08
-3.450176e-11 -9.090443e-11 -7.768342e-08 -7.261994e-08 -8.597461e-06 -3.632611e-07 -7.706134e-06 -1.317324e-12 -7.595148e-07
1.483455e-06 4.661171e-03 -6.884880e-04 -2.115217e-01 -9.364835e-04 -5.177068e-02 -1.254979e-05 3.862083e-05 1.175347e-02
4.047443e-05 3.713670e-05 -1.379101e-02 -2.773177e-04 -3.657457e-02 -1.531191e-04 -1.769128e-02 2.499450e-07 1.872743e-01
5.323889e-08 8.921723e-02 6.708379e-03 -1.844980e-01 1.048615e-03 1.596218e-02 -2.769383e-05 1.444847e-07 1.005949e-03
3.682382e-06 1.282240e-04 3.301771e-01 1.360682e-03 -4.707971e-02 1.096983e-03 1.790163e-02 2.165260e-08 -4.448259e-04
[,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26] [,27]
4.130878e-04 2.107742e-05 -4.975967e-02 -7.544341e-05 6.368708e-07 5.573879e-09 -5.524864e-03 3.157755e-06 -1.806840e-02
-1.087641e-03 -5.743470e-06 1.673679e-02 1.151636e-04 2.135991e-06 1.694732e-08 -1.595370e-03 3.499191e-06 4.151006e-03
6.326398e-03 8.947987e-04 -1.892785e-03 -2.561342e-04 -9.643205e-08 -2.672746e-10 1.310796e-02 7.249782e-04 -1.477690e-03
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1.116032e-06 2.869437e-10 6.535536e-07 3.426163e-09 -2.562365e-12 -3.541337e-13 1.063025e-05 8.770457e-08 1.051161e-06
7.689642e-08 -8.815555e-06 -4.457709e-08 1.087427e-06 -7.880084e-13 -3.450176e-11 1.483455e-06 4.047443e-05 5.323889e-08
6.150664e-02 2.459809e-04 -2.089977e-04 -1.232699e-05 2.600275e-08 -9.090443e-11 4.661171e-03 3.713670e-05 8.921723e-02
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4.163459e+00 2.143289e-03 -1.517120e-01 -1.395542e-04 9.327295e-07 6.123641e-09 7.325413e-02 1.263834e-03 2.096324e+00
2.143289e-03 7.773279e+00 7.615210e-04 4.836602e-02 1.673359e-08 1.629840e-06 -1.978241e-04 -6.983178e-02 8.294863e-04
-1.517120e-01 7.615210e-04 6.381873e+00 -1.706296e-02 5.122834e-05 1.724851e-07 1.997388e-02 3.903511e-04 -1.316587e-01
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9.327295e-07 1.673359e-08 5.122834e-05 -6.006520e-07 6.580981e-05 -3.654483e-11 1.677686e-06 -4.933806e-08 7.725429e-07
6.123641e-09 1.629840e-06 1.724851e-07 -6.206556e-07 -3.654483e-11 5.042602e-05 -4.414987e-08 -1.261128e-06 5.156091e-09
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2.096324e+00 8.294863e-04 -1.316587e-01 -1.280320e-03 7.725429e-07 5.156091e-09 8.642176e-02 1.112837e-03 7.967526e+00
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[,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35]
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3.301771e-01 2.664065e-04 -3.265108e-01 -2.530802e-03 6.964577e-02 3.757299e-03 1.256601e-01 -2.124746e+00
1.360682e-03 4.006361e-01 2.401440e-03 4.435018e-01 3.171134e-03 1.718547e+00 -4.395128e-04 -4.029830e+01
-4.707971e-02 -1.119001e-03 -9.524887e-01 6.070144e-04 -2.621125e-01 2.795584e-02 -2.727400e-01 -1.621998e+01
1.096983e-03 4.843734e-01 1.277907e-04 5.999173e-01 9.479997e-03 7.503544e-01 1.318917e-03 -3.813422e+01
1.790163e-02 1.615325e-03 1.317023e-01 4.936278e-03 -1.653512e-01 1.717751e-02 2.224564e-01 -8.852333e+00
2.165260e-08 2.156973e-05 1.531343e-07 1.216068e-05 3.237014e-08 2.347271e-05 2.333424e-07 -3.553942e-04
-4.448259e-04 4.596092e-03 3.892882e-01 7.690336e-03 2.065172e-01 9.789057e-03 2.340366e-01 -3.969899e+00
1.546872e-03 3.602447e-01 1.319812e-04 3.877252e-01 -8.422117e-04 2.043456e+00 2.542471e-04 -1.895627e+01
2.084293e-01 1.145925e-03 -1.516239e+00 -2.342256e-02 2.249494e+00 1.956533e-02 4.084740e-01 -1.378275e+01
-7.516814e-04 5.961189e-03 6.372762e-03 -1.804802e-01 3.859804e-03 1.178360e-01 2.061606e-03 -2.150542e+01
-3.319614e-01 8.753924e-04 -5.096577e-01 8.267062e-03 -1.487580e-01 -3.576956e-03 -5.207596e-02 -5.046148e+00
-3.599597e-08 -4.041343e-08 4.452367e-08 4.030344e-05 4.795860e-07 -1.185712e-05 -7.455456e-07 -8.628078e-04
8.111764e-07 1.659950e-07 5.315215e-06 5.092938e-08 1.455300e-05 8.230839e-07 2.047104e-05 -1.994034e-04
1.979182e-03 1.403369e-01 5.380428e-03 -2.327774e-01 1.238792e-02 2.722891e-01 5.228962e-03 -2.433305e+01
1.328819e-02 2.394346e-03 4.751751e-02 6.237748e-03 2.248064e-01 4.839937e-03 1.971381e-01 -4.246845e+00
5.692828e-03 1.442915e-02 -1.070577e-03 -1.127369e-01 -4.036508e-03 6.703618e-03 -3.794700e-03 -2.351528e+01
4.696572e+00 1.986515e-03 -7.995356e-01 -6.053670e-03 -3.215859e-01 -7.179484e-03 -1.594099e-02 -7.194074e+00
[ getOption("max.print") est atteint -- 7 lignes omises ]
Model rank = 7802 / 7802
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00e+00 7.17e+00 1.03 0.96
s(measurement.no):toneBis.ord1 9.00e+00 1.62e+00 1.03 0.98
s(measurement.no):toneBis.ord2 9.00e+00 1.70e+00 1.03 0.97
s(measurement.no):toneBis.ord3 9.00e+00 2.00e+00 1.03 0.99
s(measurement.no,speaker) 1.00e+02 2.23e+01 1.03 0.98
s(measurement.no,speaker):toneBis.ord1 1.00e+02 1.74e+01 1.03 0.98
s(measurement.no,speaker):toneBis.ord2 1.00e+02 7.92e-04 1.03 0.97
s(measurement.no,speaker):toneBis.ord3 1.00e+02 4.91e+00 1.03 0.99
s(measurement.no,speakerLeftRightTone) 6.00e+02 1.13e+02 1.03 0.98
s(measurement.no,speakerLeftRightTone):toneBis.ord1 6.00e+02 9.40e+01 1.03 0.97
s(measurement.no,speakerLeftRightTone):toneBis.ord2 6.00e+02 7.94e+00 1.03 0.97
s(measurement.no,speakerLeftRightTone):toneBis.ord3 6.00e+02 6.55e+01 1.03 0.99
s(measurement.no,speakerPos) 3.00e+02 5.31e+01 1.03 0.98
s(measurement.no,speakerPos):toneBis.ord1 3.00e+02 2.36e-03 1.03 0.99
s(measurement.no,speakerPos):toneBis.ord2 3.00e+02 5.72e+01 1.03 0.99
s(measurement.no,speakerPos):toneBis.ord3 3.00e+02 6.14e+01 1.03 0.96
s(measurement.no,word) 9.75e+02 3.38e+02 1.03 0.98
s(measurement.no,wordPos) 1.43e+03 4.17e+02 1.03 0.95
s(measurement.no,wordLeftRightTone) 1.36e+03 5.01e+02 1.03 0.99
# Plotting
# Normalized scale
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model1g, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", ylim = c(-1, 1), lwd = 4, xlab = "Time (normalized)", ylab = "F2 (Z)", xaxt = "n", font.lab = 2)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1g, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"), col = "orange", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1g, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"), col = "chartreuse4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1g, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"), col = "royalblue4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
legend("topright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)# Plotting
# Reconstructed scale
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model1g, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", ylim = c(1050, 1350), xlab = "Time (ms)", ylab = "F2 (Hz)", xaxt = "n", font.lab = 2, add = F, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT1au * 0.1, transform = function(f2Zscore2) f2Zscore2 * global_sd2au + global_mean2au, hide.label = TRUE)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1g, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"), col = "royalblue4", lwd = 4, add = T, transform.view = function(measurement.no) measurement.no * durationT4au * 0.1, transform = function(f2Zscore2) f2Zscore2 * global_sd2au + global_mean2au)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1g, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"), col = "orange", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT2au * 0.1, transform = function(f2Zscore2) f2Zscore2 * global_sd2au + global_mean2au)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1g, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"), col = "chartreuse4", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT3au * 0.1, transform = function(f2Zscore2) f2Zscore2 * global_sd2au + global_mean2au)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
legend("top", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)# Plotting
# Difference plot between tones
par(mfcol = c(2, 3), mar = c(2, 2, 2, 1), oma = c(4, 4, 2, 1))
plot_diff(gamm.model1g, view="measurement.no", comp=list(toneBis.ord = c("1","2")),rm.ranef=TRUE, main = "1-2", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
plot_diff(gamm.model1g, view="measurement.no",comp=list(toneBis.ord = c("1","3")),rm.ranef=TRUE, main = "1-3", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
plot_diff(gamm.model1g, view="measurement.no",comp=list(toneBis.ord = c("1","4")),rm.ranef=TRUE, main = "1-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
plot_diff(gamm.model1g, view="measurement.no",comp=list(toneBis.ord = c("2","3")),rm.ranef=TRUE, main = "2-3", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
plot_diff(gamm.model1g, view="measurement.no",comp=list(toneBis.ord = c("2","4")),rm.ranef=TRUE, main = "2-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
plot_diff(gamm.model1g, view="measurement.no",comp=list(toneBis.ord = c("3","4")),rm.ranef=TRUE, main = "3-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
Difference is not significant.
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
mtext("Difference in F2 (Z)", side = 2, outer = TRUE, line = 2.5, cex = 1.2, font = 2)plot_parametric(gamm.model1g, pred = list(toneBis.ord=c("1", "2", "3", "4")), xlab = "F2 (Z)", main = "Tone")Summary:
* toneBis.ord : factor; set to the value(s): 1, 2, 3, 4.
* measurement.no : numeric predictor; set to the value(s): 5.
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
gamm.model1h <- bam(f2Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.au.fem, method="fREML", discrete = TRUE, nthreads = ncores)# Auto-regressive model
gamm.model1h <- bam(f2Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr") +
# random effects
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1, by=toneBis.ord) +
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1),
data=data.au.fem, method="fREML", rho = r.gamm.model1h, AR.start = data.au.fem$start, discrete = TRUE, nthreads = ncores)
Family: gaussian
Link function: identity
Formula:
f2Zscore2 ~ toneBis.ord + s(measurement.no, bs = "cr") + s(measurement.no,
by = toneBis.ord, bs = "cr") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speaker, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = toneBis.ord) + s(measurement.no, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1, by = toneBis.ord) + s(measurement.no, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerPos, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1,
by = toneBis.ord) + s(measurement.no, word, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordPos, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, wordLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 3, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.05552 0.04806 1.155 0.248053
toneBis.ord1 -0.31831 0.08609 -3.697 0.000219 ***
toneBis.ord2 -0.16235 0.13889 -1.169 0.242453
toneBis.ord3 0.02006 0.08500 0.236 0.813438
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 7.332 7.724 32.386 < 2e-16 ***
s(measurement.no):toneBis.ord1 3.735 4.515 1.410 0.25469
s(measurement.no):toneBis.ord2 1.000 1.000 8.169 0.00427 **
s(measurement.no):toneBis.ord3 3.550 4.198 3.324 0.00813 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.744 Deviance explained = 78.7%
fREML = 8049 Scale est. = 0.2311 n = 10252
Method: fREML Optimizer: perf chol
$grad
[1] -2.056133e-13 -9.925394e-14 -5.381781e-05 7.482903e-14 2.238210e-13 -9.080208e-05 -5.604331e-05 -1.954764e-06 -3.857644e-05
[10] -5.551115e-15 3.552714e-15 -7.882583e-15 2.771117e-13 1.776357e-14 -4.618528e-13 -3.019807e-14 -1.953993e-13 -9.503509e-14
[19] -3.552714e-14 -8.881784e-15 -2.202682e-13 -6.661338e-14 -7.620288e-05 -2.547962e-14 -5.329071e-14 -9.316737e-05 -1.172396e-13
[28] -2.753353e-14 5.684342e-14 -1.989520e-13 -6.536993e-13 -1.136868e-13 -1.705303e-13 7.105427e-15 -5.456968e-12
$hess
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
2.886506e+00 -8.165956e-02 4.205714e-06 4.235402e-02 3.969066e-02 7.414044e-09 -9.806132e-07 -5.454388e-09 9.803514e-07
-8.165956e-02 5.854181e-01 3.361882e-06 4.546892e-02 -1.799790e-02 -1.986621e-08 5.026616e-06 -6.151380e-08 5.854191e-07
4.205714e-06 3.361882e-06 5.381423e-05 -8.825209e-06 -2.121406e-06 -5.018114e-12 -2.242107e-11 1.066201e-12 2.452243e-10
4.235402e-02 4.546892e-02 -8.825209e-06 9.564489e-01 -2.190838e-02 -3.053887e-08 3.316095e-07 -5.468488e-08 -1.097971e-06
3.969066e-02 -1.799790e-02 -2.121406e-06 -2.190838e-02 1.300605e+01 -1.472137e-06 -9.948271e-07 -8.124166e-07 -3.023621e-06
7.414044e-09 -1.986621e-08 -5.018114e-12 -3.053887e-08 -1.472137e-06 9.080134e-05 -2.037248e-12 -7.149893e-09 1.366655e-12
-9.806132e-07 5.026616e-06 -2.242107e-11 3.316095e-07 -9.948271e-07 -2.037248e-12 5.604629e-05 6.602073e-10 -3.924320e-11
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9.803514e-07 5.854191e-07 2.452243e-10 -1.097971e-06 -3.023621e-06 1.366655e-12 -3.924320e-11 -4.942095e-12 3.858004e-05
1.396230e-05 -1.406249e-05 6.633962e-08 -1.900635e-04 -7.678157e-04 -3.554136e-07 4.994476e-09 2.585219e-06 7.533450e-08
9.376440e-03 3.573732e-03 -6.001278e-07 2.180237e-02 2.655765e-02 7.471867e-08 8.484395e-07 2.837683e-07 -7.046646e-07
-6.808330e-06 -1.959267e-05 7.773505e-09 1.268144e-04 -2.564425e-04 -1.033468e-06 2.932959e-10 1.470165e-06 1.861346e-09
1.072305e-01 -2.293115e-03 -1.249674e-06 2.594501e-02 2.915698e+00 -4.124312e-07 -2.296648e-06 -2.553101e-07 -1.367543e-05
-5.113264e-05 1.407438e-04 -4.736159e-09 -4.440147e-04 -2.015467e-02 7.257574e-06 -8.948578e-08 -4.725988e-05 7.320647e-08
-1.206730e-02 1.124403e-01 -1.493274e-06 1.918102e-04 1.506926e-01 -1.993904e-07 6.519124e-05 1.284654e-05 5.939598e-07
1.142488e-04 5.683852e-04 6.149664e-09 2.246579e-04 -3.118093e-03 -1.130600e-05 1.477604e-06 5.663082e-04 8.979453e-09
2.200695e-02 -1.333230e-02 1.241474e-05 -1.086276e-02 -7.985877e-03 1.077522e-07 -1.042582e-06 -3.797280e-07 1.185975e-04
3.913438e-05 1.639885e-06 1.393471e-07 -4.512330e-04 -2.294813e-03 -2.518078e-06 1.972913e-08 2.624094e-06 3.919648e-07
1.777503e-02 -4.356595e-03 -2.078651e-06 1.281784e-01 -1.006199e-02 2.349787e-07 6.891805e-09 3.842853e-07 -1.808104e-06
-3.862066e-04 -7.429886e-04 1.297983e-08 2.257717e-03 1.347356e-03 -6.810254e-06 -1.810731e-08 2.214223e-05 1.053697e-08
-1.469443e-02 2.264674e-03 2.490395e-06 1.501686e-02 1.841689e+00 -2.522577e-07 4.834629e-06 -1.025341e-06 4.169355e-06
2.984468e-04 4.180668e-05 -2.001799e-07 -6.658631e-04 -9.969294e-03 -7.344100e-06 -8.820564e-08 -3.436731e-05 1.314116e-08
-1.070262e-06 3.650026e-06 -2.750601e-11 5.192212e-07 1.308526e-05 9.138350e-13 3.188189e-09 7.804734e-10 -1.924734e-11
5.899755e-06 -4.036605e-05 -7.390840e-10 -1.552603e-06 3.510216e-04 -5.981947e-07 8.665276e-08 2.355309e-05 3.739131e-10
9.899997e-03 4.437641e-03 8.036792e-06 -6.254622e-03 -2.712646e-02 -4.790932e-08 -7.759347e-07 -1.881713e-07 6.061738e-05
-3.004297e-08 -8.786602e-08 1.636921e-11 2.189748e-07 -5.196137e-08 7.865171e-11 4.153039e-12 1.002061e-09 2.358607e-11
1.748174e-03 2.190495e-04 -1.256478e-07 2.572225e-02 3.933658e-02 5.137537e-09 1.373502e-07 1.381352e-07 -7.890231e-07
-1.017652e-04 -4.262670e-04 6.334965e-08 1.175215e-03 -1.018894e-03 -3.479467e-06 -1.500264e-08 7.517212e-06 2.536061e-08
[,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18]
1.396230e-05 9.376440e-03 -6.808330e-06 1.072305e-01 -5.113264e-05 -1.206730e-02 1.142488e-04 2.200695e-02 3.913438e-05
-1.406249e-05 3.573732e-03 -1.959267e-05 -2.293115e-03 1.407438e-04 1.124403e-01 5.683852e-04 -1.333230e-02 1.639885e-06
6.633962e-08 -6.001278e-07 7.773505e-09 -1.249674e-06 -4.736159e-09 -1.493274e-06 6.149664e-09 1.241474e-05 1.393471e-07
-1.900635e-04 2.180237e-02 1.268144e-04 2.594501e-02 -4.440147e-04 1.918102e-04 2.246579e-04 -1.086276e-02 -4.512330e-04
-7.678157e-04 2.655765e-02 -2.564425e-04 2.915698e+00 -2.015467e-02 1.506926e-01 -3.118093e-03 -7.985877e-03 -2.294813e-03
-3.554136e-07 7.471867e-08 -1.033468e-06 -4.124312e-07 7.257574e-06 -1.993904e-07 -1.130600e-05 1.077522e-07 -2.518078e-06
4.994476e-09 8.484395e-07 2.932959e-10 -2.296648e-06 -8.948578e-08 6.519124e-05 1.477604e-06 -1.042582e-06 1.972913e-08
2.585219e-06 2.837683e-07 1.470165e-06 -2.553101e-07 -4.725988e-05 1.284654e-05 5.663082e-04 -3.797280e-07 2.624094e-06
7.533450e-08 -7.046646e-07 1.861346e-09 -1.367543e-05 7.320647e-08 5.939598e-07 8.979453e-09 1.185975e-04 3.919648e-07
7.933819e-02 -2.047914e-04 1.096834e-03 -1.195762e-04 -1.883057e-02 1.730831e-04 7.190810e-03 4.068010e-03 4.107291e-01
-2.047914e-04 5.351787e-01 2.594692e-03 1.282930e-02 1.684367e-04 1.461684e-02 -1.514458e-04 -4.238278e-03 -5.753731e-05
1.096834e-03 2.594692e-03 2.048069e-02 3.334529e-05 -1.156569e-02 -5.072850e-05 2.091834e-03 2.170208e-06 8.626483e-03
-1.195762e-04 1.282930e-02 3.334529e-05 1.435264e+01 4.791918e-02 1.007960e+00 1.982998e-03 -6.172665e-01 -3.907466e-03
-1.883057e-02 1.684367e-04 -1.156569e-02 4.791918e-02 8.618028e+00 8.347341e-06 -7.081581e-04 4.346679e-03 -1.938123e-01
1.730831e-04 1.461684e-02 -5.072850e-05 1.007960e+00 8.347341e-06 1.162960e+01 5.817242e-02 -2.117739e-02 1.616569e-03
7.190810e-03 -1.514458e-04 2.091834e-03 1.982998e-03 -7.081581e-04 5.817242e-02 5.746728e+00 5.947032e-04 3.575333e-02
4.068010e-03 -4.238278e-03 2.170208e-06 -6.172665e-01 4.346679e-03 -2.117739e-02 5.947032e-04 7.532931e+00 5.418699e-02
4.107291e-01 -5.753731e-05 8.626483e-03 -3.907466e-03 -1.938123e-01 1.616569e-03 3.575333e-02 5.418699e-02 3.116018e+00
9.411679e-04 9.884525e-01 3.781443e-03 -3.380966e-01 1.804735e-03 5.765664e-02 -8.456714e-05 1.134806e-01 7.192935e-03
3.142429e-02 1.632188e-02 1.083723e-01 -2.615276e-03 -6.221225e-01 -3.002136e-03 5.590658e-02 2.397540e-03 1.606300e-01
2.711764e-04 4.154280e-02 9.510881e-05 1.007055e+00 -1.374389e-02 -2.103386e-01 -6.217315e-03 1.506407e-01 3.570076e-03
2.714099e-02 1.105886e-03 -8.834764e-03 2.218211e-03 2.703374e-01 -5.023120e-03 -1.831192e-01 2.369937e-03 1.312044e-01
-3.613284e-09 8.300473e-07 -1.179357e-09 1.146377e-05 -5.910111e-08 1.075408e-04 1.586930e-06 -1.131739e-07 -3.705227e-08
1.661186e-03 3.244934e-07 8.194045e-05 1.092027e-04 -1.394831e-02 1.660074e-03 7.754395e-02 6.928677e-05 9.060316e-03
2.449292e-03 2.168689e-02 2.649863e-04 -1.497470e-01 1.881975e-03 -4.552947e-03 9.060298e-04 2.714276e+00 2.794188e-02
6.171795e-05 1.465217e-06 -3.277593e-06 -8.284783e-07 1.877677e-05 4.280971e-07 -3.755343e-07 6.161042e-06 4.014409e-04
1.349794e-04 2.393237e-01 1.184016e-03 1.494030e-01 3.073656e-04 -6.045488e-06 1.858074e-04 -8.130998e-02 1.071648e-03
4.450671e-03 1.235016e-02 9.063413e-02 -2.364311e-03 -8.753786e-02 -1.215969e-03 -9.845598e-02 5.441616e-04 1.194015e-02
[,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26] [,27]
1.777503e-02 -3.862066e-04 -1.469443e-02 2.984468e-04 -1.070262e-06 5.899755e-06 9.899997e-03 -3.004297e-08 1.748174e-03
-4.356595e-03 -7.429886e-04 2.264674e-03 4.180668e-05 3.650026e-06 -4.036605e-05 4.437641e-03 -8.786602e-08 2.190495e-04
-2.078651e-06 1.297983e-08 2.490395e-06 -2.001799e-07 -2.750601e-11 -7.390840e-10 8.036792e-06 1.636921e-11 -1.256478e-07
1.281784e-01 2.257717e-03 1.501686e-02 -6.658631e-04 5.192212e-07 -1.552603e-06 -6.254622e-03 2.189748e-07 2.572225e-02
-1.006199e-02 1.347356e-03 1.841689e+00 -9.969294e-03 1.308526e-05 3.510216e-04 -2.712646e-02 -5.196137e-08 3.933658e-02
2.349787e-07 -6.810254e-06 -2.522577e-07 -7.344100e-06 9.138350e-13 -5.981947e-07 -4.790932e-08 7.865171e-11 5.137537e-09
6.891805e-09 -1.810731e-08 4.834629e-06 -8.820564e-08 3.188189e-09 8.665276e-08 -7.759347e-07 4.153039e-12 1.373502e-07
3.842853e-07 2.214223e-05 -1.025341e-06 -3.436731e-05 7.804734e-10 2.355309e-05 -1.881713e-07 1.002061e-09 1.381352e-07
-1.808104e-06 1.053697e-08 4.169355e-06 1.314116e-08 -1.924734e-11 3.739131e-10 6.061738e-05 2.358607e-11 -7.890231e-07
9.411679e-04 3.142429e-02 2.711764e-04 2.714099e-02 -3.613284e-09 1.661186e-03 2.449292e-03 6.171795e-05 1.349794e-04
9.884525e-01 1.632188e-02 4.154280e-02 1.105886e-03 8.300473e-07 3.244934e-07 2.168689e-02 1.465217e-06 2.393237e-01
3.781443e-03 1.083723e-01 9.510881e-05 -8.834764e-03 -1.179357e-09 8.194045e-05 2.649863e-04 -3.277593e-06 1.184016e-03
-3.380966e-01 -2.615276e-03 1.007055e+00 2.218211e-03 1.146377e-05 1.092027e-04 -1.497470e-01 -8.284783e-07 1.494030e-01
1.804735e-03 -6.221225e-01 -1.374389e-02 2.703374e-01 -5.910111e-08 -1.394831e-02 1.881975e-03 1.877677e-05 3.073656e-04
5.765664e-02 -3.002136e-03 -2.103386e-01 -5.023120e-03 1.075408e-04 1.660074e-03 -4.552947e-03 4.280971e-07 -6.045488e-06
-8.456714e-05 5.590658e-02 -6.217315e-03 -1.831192e-01 1.586930e-06 7.754395e-02 9.060298e-04 -3.755343e-07 1.858074e-04
1.134806e-01 2.397540e-03 1.506407e-01 2.369937e-03 -1.131739e-07 6.928677e-05 2.714276e+00 6.161042e-06 -8.130998e-02
7.192935e-03 1.606300e-01 3.570076e-03 1.312044e-01 -3.705227e-08 9.060316e-03 2.794188e-02 4.014409e-04 1.071648e-03
1.450465e+01 8.068396e-02 -2.322966e-01 -1.120044e-04 1.546342e-06 -1.326965e-04 1.352447e-01 2.191644e-06 1.472407e+00
8.068396e-02 4.994323e+00 -1.354518e-03 -7.528376e-02 -1.449636e-07 -2.281753e-04 1.081392e-02 2.796713e-05 3.716360e-03
-2.322966e-01 -1.354518e-03 6.311074e+00 1.162652e-02 -2.302263e-05 -9.332746e-04 2.509813e-01 1.159615e-06 -3.984301e-01
-1.120044e-04 -7.528376e-02 1.162652e-02 3.613317e+00 -1.749931e-07 -5.564151e-02 -6.419589e-03 3.759500e-05 1.833572e-03
1.546342e-06 -1.449636e-07 -2.302263e-05 -1.749931e-07 7.621419e-05 2.528416e-08 7.251031e-08 -9.692229e-12 1.152698e-06
-1.326965e-04 -2.281753e-04 -9.332746e-04 -5.564151e-02 2.528416e-08 2.120648e-02 1.300634e-04 1.346675e-06 -3.780534e-05
1.352447e-01 1.081392e-02 2.509813e-01 -6.419589e-03 7.251031e-08 1.300634e-04 2.841610e+00 1.035599e-06 9.122822e-03
2.191644e-06 2.796713e-05 1.159615e-06 3.759500e-05 -9.692229e-12 1.346675e-06 1.035599e-06 9.327441e-05 1.760766e-06
1.472407e+00 3.716360e-03 -3.984301e-01 1.833572e-03 1.152698e-06 -3.780534e-05 9.122822e-03 1.760766e-06 1.196596e+00
1.235850e-02 7.557761e-02 -2.835687e-03 2.676195e-01 4.582238e-08 -1.108945e-02 1.217038e-02 4.661362e-05 1.383148e-02
[,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35]
-1.017652e-04 4.258808e-02 -1.360150e-03 3.322268e-03 -9.971456e-06 7.513848e-03 -6.354940e-04 -3.165894e+00
-4.262670e-04 9.882143e-02 -1.016725e-03 3.402620e-02 6.864391e-04 8.031297e-02 -1.222000e-03 -1.367253e+00
6.334965e-08 4.306426e-07 -1.592972e-07 -9.994174e-06 -5.212644e-08 -1.112493e-05 2.342457e-07 -6.390932e-05
1.175215e-03 -1.533348e-01 1.645684e-03 -1.380154e-02 -6.476801e-04 -1.070087e-01 5.018938e-04 -1.275058e+00
-1.018894e-03 9.345435e-02 6.575828e-03 -2.739587e-01 1.417134e-03 1.539258e-01 3.241403e-03 -1.976019e+01
-3.479467e-06 8.930580e-08 -1.212004e-05 3.019437e-07 4.748293e-06 1.667192e-08 5.186820e-06 -8.710142e-05
-1.500264e-08 1.796511e-06 -1.500460e-08 1.140299e-05 -5.597067e-08 -3.728870e-06 5.989330e-09 -3.106739e-04
7.517212e-06 2.448654e-06 -5.116654e-05 2.348723e-07 -3.071005e-05 2.768391e-06 7.628962e-05 -1.035268e-03
2.536061e-08 -4.790622e-06 1.103795e-07 -5.536293e-06 -7.359308e-09 -1.054108e-05 -6.506780e-08 -3.032537e-04
4.450671e-03 -5.112386e-04 -1.321889e-02 5.654700e-04 -2.250108e-02 -2.140277e-04 3.746993e-02 -7.558734e-01
1.235016e-02 2.054230e-02 1.758034e-03 -1.710042e-02 -1.830262e-03 9.673513e-02 -9.864212e-04 -4.159457e+00
9.063413e-02 2.799252e-04 -2.023547e-03 -6.154558e-05 1.481228e-02 4.067976e-04 9.443481e-03 -3.076511e-01
-2.364311e-03 1.414336e+00 -1.346433e-02 4.423084e-01 -2.125935e-03 3.110768e+00 6.736847e-03 -4.865230e+01
-8.753786e-02 3.486488e-03 -6.946701e-01 1.001795e-02 -3.000997e-01 2.918616e-02 -2.431340e-01 -1.410859e+01
-1.215969e-03 3.614122e-01 6.535554e-03 9.034376e-01 -3.426288e-03 5.183498e-01 3.993955e-03 -4.683977e+01
-9.845598e-02 2.359391e-02 3.703734e-01 9.277112e-03 -1.266902e-01 3.311281e-02 6.289435e-01 -1.136494e+01
5.441616e-04 7.550260e-01 1.050738e-02 2.482924e-01 -2.646575e-04 1.089313e+00 2.023632e-03 -2.187818e+01
1.194015e-02 9.607222e-04 7.693279e-02 6.302139e-03 -4.182787e-02 1.570391e-02 4.390413e-01 -5.852202e+00
1.235850e-02 6.642941e-01 -1.679143e-03 6.888582e-01 1.577090e-03 9.456626e-02 8.396634e-03 -4.769336e+01
7.557761e-02 6.317578e-03 -1.998857e-01 1.910147e-02 3.861191e-01 1.644910e-02 -2.603969e-02 -1.099547e+01
-2.835687e-03 1.883312e-01 5.845969e-03 3.252394e-01 4.116890e-03 8.603551e-01 6.514449e-03 -2.017136e+01
2.676195e-01 7.188005e-04 -1.599402e-01 -7.030199e-04 -2.095657e-01 3.853118e-03 -1.421315e-01 -6.970679e+00
4.582238e-08 1.889327e-05 2.476178e-07 5.242289e-05 9.862300e-10 -9.372364e-06 -1.135426e-08 -8.807661e-04
-1.108945e-02 -6.490300e-04 -5.122356e-02 1.678026e-03 1.880673e-02 -1.564464e-03 -6.453308e-04 -4.583916e-01
1.217038e-02 1.059145e-01 1.631450e-02 3.379487e-02 -1.028514e-02 9.566842e-02 -4.237459e-03 -1.303378e+01
4.661362e-05 1.130094e-06 2.785413e-04 -3.245905e-06 -1.763910e-05 -2.415180e-06 2.538859e-05 -1.262042e-03
1.383148e-02 -3.375729e-02 2.344395e-03 4.313759e-01 1.717118e-03 1.301346e-01 1.109539e-03 -9.207264e+00
3.299539e+00 -3.034153e-03 -5.597238e-01 8.277296e-03 1.232575e-01 -5.090926e-04 -1.322615e-01 -6.145576e+00
[ getOption("max.print") est atteint -- 7 lignes omises ]
Model rank = 7542 / 7542
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00e+00 7.33e+00 0.99 0.17
s(measurement.no):toneBis.ord1 9.00e+00 3.73e+00 0.99 0.17
s(measurement.no):toneBis.ord2 9.00e+00 1.00e+00 0.99 0.10
s(measurement.no):toneBis.ord3 9.00e+00 3.55e+00 0.99 0.16
s(measurement.no,speaker) 1.00e+02 3.95e+01 0.99 0.17
s(measurement.no,speaker):toneBis.ord1 1.00e+02 2.81e-03 0.99 0.21
s(measurement.no,speaker):toneBis.ord2 1.00e+02 1.51e+00 0.99 0.17
s(measurement.no,speaker):toneBis.ord3 1.00e+02 8.93e+00 0.99 0.18
s(measurement.no,speakerLeftRightTone) 5.80e+02 1.26e+02 0.99 0.14
s(measurement.no,speakerLeftRightTone):toneBis.ord1 5.80e+02 1.16e+02 0.99 0.15
s(measurement.no,speakerLeftRightTone):toneBis.ord2 5.80e+02 5.55e+01 0.99 0.19
s(measurement.no,speakerLeftRightTone):toneBis.ord3 5.80e+02 1.17e+02 0.99 0.13
s(measurement.no,speakerPos) 3.00e+02 5.43e+01 0.99 0.15
s(measurement.no,speakerPos):toneBis.ord1 3.00e+02 9.19e-01 0.99 0.12
s(measurement.no,speakerPos):toneBis.ord2 3.00e+02 2.61e+01 0.99 0.21
s(measurement.no,speakerPos):toneBis.ord3 3.00e+02 3.07e+01 0.99 0.10
s(measurement.no,word) 9.30e+02 3.86e+02 0.99 0.19
s(measurement.no,wordPos) 1.39e+03 3.36e+02 0.99 0.19
s(measurement.no,wordLeftRightTone) 1.27e+03 4.18e+02 0.99 0.21
# Plotting
# Normalized scale
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model1h, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", ylim = c(-1, 1), lwd = 4, xlab = "Time (normalized)", ylab = "F2 (Z)", xaxt = "n", font.lab = 2)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1h, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"), col = "orange", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1h, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"), col = "chartreuse4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
plot_smooth(gamm.model1h, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"), col = "royalblue4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
legend("topright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)# Plotting
# Reconstructed scale
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model1h, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"), col = "orange", ylim = c(1150, 1600), xlab = "Time (ms)", ylab = "F2 (Hz)", xaxt = "n", font.lab = 2, add = F, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT2auf * 0.1, transform = function(f2Zscore2) f2Zscore2 * global_sd2auf + global_mean2auf, hide.label = TRUE)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1h, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"), col = "royalblue4", lwd = 4, add = T, transform.view = function(measurement.no) measurement.no * durationT4auf * 0.1, transform = function(f2Zscore2) f2Zscore2 * global_sd2auf + global_mean2auf)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1h, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT1auf * 0.1, transform = function(f2Zscore2) f2Zscore2 * global_sd2auf + global_mean2auf)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model1h, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"), col = "chartreuse4", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * durationT3auf * 0.1, transform = function(f2Zscore2) f2Zscore2 * global_sd2auf + global_mean2auf)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
* Note: X-values are transformed.
legend("top", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=4)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)# Plotting
# Difference plot between tones
par(mfcol = c(2, 3), mar = c(2, 2, 2, 1), oma = c(4, 4, 2, 1))
plot_diff(gamm.model1h, view="measurement.no", comp=list(toneBis.ord = c("1","2")),rm.ranef=TRUE, main = "1-2", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.000000 - 3.232323
plot_diff(gamm.model1h, view="measurement.no",comp=list(toneBis.ord = c("1","3")),rm.ranef=TRUE, main = "1-3", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.000000 - 4.545455
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
plot_diff(gamm.model1h, view="measurement.no",comp=list(toneBis.ord = c("1","4")),rm.ranef=TRUE, main = "1-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.000000 - 10.000000
plot_diff(gamm.model1h, view="measurement.no",comp=list(toneBis.ord = c("2","3")),rm.ranef=TRUE, main = "2-3", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
9.191919 - 10.000000
plot_diff(gamm.model1h, view="measurement.no",comp=list(toneBis.ord = c("2","4")),rm.ranef=TRUE, main = "2-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
6.666667 - 10.000000
plot_diff(gamm.model1h, view="measurement.no",comp=list(toneBis.ord = c("3","4")),rm.ranef=TRUE, main = "3-4", hide.label = T, xaxt = "n", xlab = "", ylab = "")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
measurement.no window(s) of significant difference(s):
0.000000 - 1.515152
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
mtext("Difference in F2 (Z)", side = 2, outer = TRUE, line = 2.5, cex = 1.2, font = 2)plot_parametric(gamm.model1h, pred = list(toneBis.ord=c("1", "2", "3", "4")), xlab = "F2 (Z)", main = "Tone")Summary:
* toneBis.ord : factor; set to the value(s): 1, 2, 3, 4.
* measurement.no : numeric predictor; set to the value(s): 5.
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(measurement.no,speaker),s(measurement.no,speaker):toneBis.ord1,s(measurement.no,speaker):toneBis.ord2,s(measurement.no,speaker):toneBis.ord3,s(measurement.no,speakerLeftRightTone),s(measurement.no,speakerLeftRightTone):toneBis.ord1,s(measurement.no,speakerLeftRightTone):toneBis.ord2,s(measurement.no,speakerLeftRightTone):toneBis.ord3,s(measurement.no,speakerPos),s(measurement.no,speakerPos):toneBis.ord1,s(measurement.no,speakerPos):toneBis.ord2,s(measurement.no,speakerPos):toneBis.ord3,s(measurement.no,word),s(measurement.no,wordPos),s(measurement.no,wordLeftRightTone)
gamm.model2test.noAR <- bam(f1Zscore2 ~
# smooth
s(measurement.no, bs="cr") +
s(f0Zscore2, bs="cr") +
s(durationZscore2, bs="cr") +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr") +
ti(measurement.no, durationZscore2, bs = "cr") +
ti(measurement.no, f0Zscore2, bs = "cr") +
ti(f0Zscore2, durationZscore2, bs = "cr") +
# random effect
## left segment * pow
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(durationZscore2, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(f0Zscore2, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(durationZscore2, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(f0Zscore2, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(durationZscore2, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(f0Zscore2, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=5, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=5, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=5, m=1),
data=data.ai.mas, method="fREML", discrete = TRUE, nthreads = ncores)# Auto-regressive model
gamm.model2test <- bam(f1Zscore2 ~
# smooth
s(measurement.no, bs="cr") +
s(f0Zscore2, bs="cr") +
s(durationZscore2, bs="cr") +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr") +
ti(measurement.no, durationZscore2, bs = "cr") +
ti(measurement.no, f0Zscore2, bs = "cr") +
ti(f0Zscore2, durationZscore2, bs = "cr") +
# random effect
## left segment * pow
s(measurement.no, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(durationZscore2, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(f0Zscore2, word, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(durationZscore2, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(f0Zscore2, wordLeftRightTone, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(durationZscore2, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(f0Zscore2, wordPos, bs="fs", xt = list(bs="tp"), k=3, m=1) +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=5, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=5, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=5, m=1),
data=data.ai.mas, method="fREML", discrete = TRUE, nthreads = ncores, rho = r.gamm.model2test, AR.start = data.ai.mas$start)
Family: gaussian
Link function: identity
Formula:
f1Zscore2 ~ s(measurement.no, bs = "cr") + s(f0Zscore2, bs = "cr") +
s(durationZscore2, bs = "cr") + ti(measurement.no, f0Zscore2,
durationZscore2, bs = "cr") + ti(measurement.no, durationZscore2,
bs = "cr") + ti(measurement.no, f0Zscore2, bs = "cr") + ti(f0Zscore2,
durationZscore2, bs = "cr") + s(measurement.no, word, bs = "fs",
xt = list(bs = "tp"), k = 3, m = 1) + s(durationZscore2,
word, bs = "fs", xt = list(bs = "tp"), k = 3, m = 1) + s(f0Zscore2,
word, bs = "fs", xt = list(bs = "tp"), k = 3, m = 1) + s(measurement.no,
wordLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 3,
m = 1) + s(durationZscore2, wordLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 3, m = 1) + s(f0Zscore2, wordLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 3, m = 1) + s(measurement.no,
wordPos, bs = "fs", xt = list(bs = "tp"), k = 3, m = 1) +
s(durationZscore2, wordPos, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(f0Zscore2, wordPos, bs = "fs", xt = list(bs = "tp"),
k = 3, m = 1) + s(measurement.no, speaker, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(durationZscore2, speaker, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(measurement.no, speakerPos, bs = "fs",
xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speakerPos, bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) +
s(f0Zscore2, speakerPos, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(measurement.no, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 5, m = 1) + s(durationZscore2,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 5,
m = 1) + s(f0Zscore2, speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"),
k = 5, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.05456 0.03976 -1.372 0.17
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 7.999 8.165 70.719 < 2e-16 ***
s(f0Zscore2) 1.000 1.000 4.159 0.0414 *
s(durationZscore2) 2.014 2.094 0.911 0.3851
ti(measurement.no,f0Zscore2,durationZscore2) 7.469 10.436 0.978 0.3984
ti(measurement.no,durationZscore2) 8.978 10.828 18.751 < 2e-16 ***
ti(measurement.no,f0Zscore2) 7.295 8.907 5.030 8.86e-07 ***
ti(f0Zscore2,durationZscore2) 3.516 4.304 1.386 0.2594
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.765 Deviance explained = 79.9%
fREML = 5915.7 Scale est. = 0.13714 n = 11029
Method: fREML Optimizer: perf chol
$grad
[1] 7.327472e-14 -5.359783e-05 -1.103562e-13 -1.332268e-14 -6.039613e-14 -2.509104e-14
[7] -3.752554e-14 3.641532e-14 5.750955e-14 -1.971756e-13 -4.329870e-14 -1.409983e-14
[13] 2.842171e-14 1.509903e-13 -7.198618e-05 1.669775e-13 -9.287826e-05 -3.677059e-13
[19] 3.410605e-13 -1.154632e-13 -7.460699e-14 5.506706e-14 1.278977e-13 1.243450e-13
[25] 1.421085e-14 -1.119105e-13 -9.237056e-14 -6.927792e-14 3.126388e-13 -1.776357e-15
[31] 3.623768e-13 -1.845746e-15 7.105427e-15 1.666722e-14 -7.105427e-14 6.078471e-15
[37] 8.881784e-14 -5.018208e-14 -4.121148e-13 -1.021405e-14 -1.776357e-13 3.019807e-14
[43] -7.815970e-14 8.437695e-14 6.608047e-13 1.776357e-14 2.131628e-13 -1.438849e-13
[49] -1.818989e-12
$hess
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[,43] [,44] [,45] [,46] [,47] [,48]
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[ getOption("max.print") est atteint -- 29 lignes omises ]
Model rank = 9875 / 9875
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00 8.00 0.98 0.14
s(f0Zscore2) 9.00 1.00 1.00 0.51
s(durationZscore2) 9.00 2.01 0.94 <2e-16 ***
ti(measurement.no,f0Zscore2,durationZscore2) 64.00 7.47 1.00 0.40
ti(measurement.no,durationZscore2) 16.00 8.98 0.99 0.17
ti(measurement.no,f0Zscore2) 16.00 7.30 1.00 0.61
ti(f0Zscore2,durationZscore2) 16.00 3.52 0.95 <2e-16 ***
s(measurement.no,word) 627.00 96.83 0.98 0.09 .
s(durationZscore2,word) 627.00 13.43 0.94 <2e-16 ***
s(f0Zscore2,word) 627.00 13.43 1.00 0.52
s(measurement.no,wordLeftRightTone) 930.00 290.59 0.98 0.10
s(durationZscore2,wordLeftRightTone) 930.00 83.88 0.94 <2e-16 ***
s(f0Zscore2,wordLeftRightTone) 930.00 126.58 1.00 0.52
s(measurement.no,wordPos) 993.00 112.59 0.98 0.07 .
s(durationZscore2,wordPos) 993.00 101.30 0.94 <2e-16 ***
s(f0Zscore2,wordPos) 993.00 134.51 1.00 0.51
s(measurement.no,speaker) 100.00 65.87 0.98 0.14
s(durationZscore2,speaker) 100.00 13.17 0.94 <2e-16 ***
s(f0Zscore2,speaker) 100.00 42.19 1.00 0.51
s(measurement.no,speakerPos) 300.00 42.17 0.98 0.07 .
s(durationZscore2,speakerPos) 300.00 117.44 0.94 <2e-16 ***
s(f0Zscore2,speakerPos) 300.00 59.01 1.00 0.52
s(measurement.no,speakerLeftRightTone) 295.00 82.70 0.98 0.09 .
s(durationZscore2,speakerLeftRightTone) 295.00 95.50 0.94 <2e-16 ***
s(f0Zscore2,speakerLeftRightTone) 295.00 48.67 1.00 0.48
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Because of the high number of levels in the word
variable — for instance, in the case of the diphthong /ai/ produced by
male speakers, there were 205 distinct word types, each appearing on
average only five times. The related variables wordPos and
wordLeftRightTone contained 311 and 293 levels,
respectively. Introducing separate nonlinear effects for each of these
rarely occurring levels and increasing k values, would increase model
fitting, but at the cost of substantially greater computation time.
Moreover, simply doubling the k values failed to resolve the poor fit,
as reflected in the gam.check diagnostics.
Another structure is tested:
system.time(gamm.model2a.noAR <- bam(f1Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.ai.mas, method="fREML", discrete = TRUE, nthreads = ncores)
)system.time(gamm.model2a <- bam(f1Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.ai.mas, method="fREML", discrete = TRUE, nthreads = ncores, rho = r.gamm.model2a, AR.start = data.ai.mas$start)
)
Family: gaussian
Link function: identity
Formula:
f1Zscore2 ~ s(measurement.no, bs = "cr", k = 10) + s(f0Zscore2,
bs = "cr", k = 10) + s(durationZscore2, bs = "cr", k = 30) +
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + ti(measurement.no, durationZscore2,
bs = "cr", k = c(5, 12)) + ti(measurement.no, f0Zscore2,
bs = "cr", k = c(5, 8)) + ti(f0Zscore2, durationZscore2,
bs = "cr", k = c(8, 12)) + s(word, bs = "re") + s(wordPos,
bs = "re") + s(wordLeftRightTone, bs = "re") + s(wordPos,
measurement.no, bs = "re") + s(wordPos, f0Zscore2, bs = "re") +
s(wordPos, durationZscore2, bs = "re") + s(wordLeftRightTone,
measurement.no, bs = "re") + s(wordLeftRightTone, f0Zscore2,
bs = "re") + s(wordLeftRightTone, durationZscore2, bs = "re") +
s(word, measurement.no, bs = "re") + s(word, f0Zscore2, bs = "re") +
s(word, durationZscore2, bs = "re") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speaker, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(measurement.no, speakerPos, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(durationZscore2, speakerPos, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(durationZscore2, speakerLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.04726 0.04994 -0.946 0.344
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 7.931 8.103 78.102 < 2e-16 ***
s(f0Zscore2) 1.000 1.000 2.757 0.0969 .
s(durationZscore2) 1.883 1.926 0.843 0.4655
ti(measurement.no,f0Zscore2,durationZscore2) 39.275 58.289 1.137 0.2213
ti(measurement.no,durationZscore2) 8.530 10.584 17.884 < 2e-16 ***
ti(measurement.no,f0Zscore2) 10.303 13.169 3.641 7.66e-06 ***
ti(f0Zscore2,durationZscore2) 6.803 9.395 0.817 0.6130
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.773 Deviance explained = 80.5%
fREML = 6007.6 Scale est. = 0.13386 n = 11029
Method: fREML Optimizer: perf chol
$grad
[1] 5.462297e-14 -9.626245e-05 -5.856648e-12 2.785328e-12 5.072387e-12 2.330580e-12 -7.629453e-13 1.047162e-12 3.013145e-13
[10] 9.966250e-12 5.706546e-14 6.866285e-12 -4.843059e-11 -1.431744e-12 -6.084733e-11 6.449596e-11 6.220446e-11 -9.343033e-10
[19] 1.883365e-10 1.088480e-10 -2.186091e-09 2.705391e-11 -2.397638e-11 -7.213591e-05 6.110668e-12 -7.087024e-05 -7.877698e-11
[28] -7.087024e-05 1.065814e-14 -7.087024e-05 -2.700062e-13 1.106071e-11 -1.008971e-10 1.121658e-11 -7.982948e-12 1.112643e-11
[37] -2.032152e-12 6.528111e-12 4.175149e-11 6.549428e-12 9.016787e-12 6.595169e-12 4.829417e-09
$hess
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[ getOption("max.print") est atteint -- 20 lignes omises ]
Model rank = 8855 / 8855
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00e+00 7.93e+00 1.05 1.00
s(f0Zscore2) 9.00e+00 1.00e+00 1.00 0.56
s(durationZscore2) 2.90e+01 1.88e+00 1.00 0.42
ti(measurement.no,f0Zscore2,durationZscore2) 3.08e+02 3.93e+01 1.01 0.86
ti(measurement.no,durationZscore2) 4.40e+01 8.53e+00 0.99 0.28
ti(measurement.no,f0Zscore2) 2.80e+01 1.03e+01 0.99 0.18
ti(f0Zscore2,durationZscore2) 7.70e+01 6.80e+00 0.99 0.29
s(word) 2.09e+02 8.08e+01 NA NA
s(wordPos) 3.31e+02 5.96e+01 NA NA
s(wordLeftRightTone) 3.10e+02 5.56e+01 NA NA
s(measurement.no,wordPos) 3.31e+02 8.99e+01 NA NA
s(f0Zscore2,wordPos) 3.31e+02 5.39e+01 NA NA
s(durationZscore2,wordPos) 3.31e+02 2.80e+01 NA NA
s(measurement.no,wordLeftRightTone) 3.10e+02 1.70e+02 NA NA
s(f0Zscore2,wordLeftRightTone) 3.10e+02 7.83e+01 NA NA
s(durationZscore2,wordLeftRightTone) 3.10e+02 3.15e+01 NA NA
s(measurement.no,word) 2.09e+02 3.34e+01 NA NA
s(f0Zscore2,word) 2.09e+02 5.79e+00 NA NA
s(durationZscore2,word) 2.09e+02 1.40e-03 NA NA
s(measurement.no,speaker) 1.00e+02 6.41e+01 1.05 1.00
s(durationZscore2,speaker) 3.00e+02 9.66e+00 1.00 0.45
s(f0Zscore2,speaker) 1.00e+02 4.03e+01 1.00 0.57
s(measurement.no,speakerPos) 3.00e+02 4.86e+01 1.05 1.00
s(durationZscore2,speakerPos) 9.00e+02 1.42e+02 1.00 0.46
s(f0Zscore2,speakerPos) 3.00e+02 6.53e+01 1.00 0.55
s(measurement.no,speakerLeftRightTone) 5.90e+02 1.13e+02 1.05 1.00
s(durationZscore2,speakerLeftRightTone) 1.77e+03 2.52e+02 1.00 0.49
s(f0Zscore2,speakerLeftRightTone) 5.90e+02 5.76e+01 1.00 0.52
# absolute value of durations at 25%, 50% and 75%
duration0.15 = quantile(data.ai.mas$durationZscore2, c(0.15)) * global_sdd + global_meand
duration0.25 = quantile(data.ai.mas$durationZscore2, c(0.25)) * global_sdd + global_meand
duration0.5 = quantile(data.ai.mas$durationZscore2, c(0.5)) * global_sdd + global_meand
duration0.75 = quantile(data.ai.mas$durationZscore2, c(0.75)) * global_sdd + global_meand
duration0.85 = quantile(data.ai.mas$durationZscore2, c(0.85)) * global_sdd + global_meand# Plotting
# 3D plot
# png("pred2-1.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2a, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.25))),
ylim = quantile(data.ai.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.25 * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0 + global_mean0),
transform = function(f1Zscore2) f1Zscore2 * global_sd1 + global_mean1,
zlim = c(450,750),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.266227 to 1.296824.
* durationZscore2 : numeric predictor; set to the value(s): -0.449662795901817.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(450,750), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
# dev.off()
# png("pred2-2.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))fvisgam(gamm.model2a, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.5))),
ylim = quantile(data.ai.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.5 * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0 + global_mean0),
transform = function(f1Zscore2) f1Zscore2 * global_sd1 + global_mean1,
zlim = c(450,750),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.266227 to 1.296824.
* durationZscore2 : numeric predictor; set to the value(s): 0.0671853722597352.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(450,750), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
# dev.off()
# png("pred2-3.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))fvisgam(gamm.model2a, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.75))),
ylim = quantile(data.ai.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.75 * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0 + global_mean0),
transform = function(f1Zscore2) f1Zscore2 * global_sd1 + global_mean1,
zlim = c(450,750),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.266227 to 1.296824.
* durationZscore2 : numeric predictor; set to the value(s): 0.637773887350503.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(450,750), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)# Plotting
# 3D plot
png("pred2-1.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2a, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.25))),
ylim = quantile(data.ai.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.25 * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0 + global_mean0),
transform = function(f1Zscore2) f1Zscore2 * global_sd1 + global_mean1,
zlim = c(450,750),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, color = mapcols_pastel, nthreads = ncores, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.266227 to 1.296824.
* durationZscore2 : numeric predictor; set to the value(s): -0.449662795901817.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(450,750), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2a, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.5))),
ylim = quantile(data.ai.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.5 * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0 + global_mean0),
transform = function(f1Zscore2) f1Zscore2 * global_sd1 + global_mean1,
zlim = c(450,750),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.266227 to 1.296824.
* durationZscore2 : numeric predictor; set to the value(s): 0.0671853722597352.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(450,750), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2a, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.75))),
ylim = quantile(data.ai.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.75 * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0 + global_mean0),
transform = function(f1Zscore2) f1Zscore2 * global_sd1 + global_mean1,
zlim = c(450,750),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.266227 to 1.296824.
* durationZscore2 : numeric predictor; set to the value(s): 0.637773887350503.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(450,750), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_diff2(gamm.model2a, view=c("measurement.no","durationZscore2"),
main = "",
comp = list(f0Zscore2 = quantile(data.ai.mas$f0Zscore2, c(0.8,0.2), na.rm = T)),
ylim = quantile(data.ai.mas$durationZscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no, function(durationZscore2) durationZscore2 * global_sdd + global_meand),
print.summary = TRUE,
sim.ci = F,
show.diff = F,
alpha.diff = 0.5,
add.color.legend = FALSE, rm.ranef = TRUE,
xlab = "Time (Normalized)", ylab = "Duration (ms)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, hide.label = T)Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* durationZscore2 : numeric predictor; with 30 values ranging from -0.786628 to 1.340871.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_diff(gamm.model2a, view="measurement.no", comp=list(f0Zscore2 = quantile(data.ai.mas$f0Zscore2, c(0.8,0.2), na.rm = T)), cond = list(durationZscore2 = 1.3),
rm.ranef=TRUE, shade = F, main = "", xlab = "Time (normalized)", ylab = "Difference in F1 (Z)", xaxt = "n", font.lab = 2, cex.lab = 1, cex.axis = 1, lwd = 2, hide.label = T)Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* durationZscore2 : numeric predictor; set to the value(s): 1.3.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
Difference is not significant.
#png("diffduration1.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model2a, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(f0Zscore2 = quantile(data.ai.mas$f0Zscore2, c(0.5), na.rm=T), durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.85))), col = "black", lwd = 4, xlab = "Time (Normalized)", ylab = "F1 (Z)", font.lab = 2, xaxt = "n", hide.label = T)Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; set to the value(s): -0.0524849620085245.
* durationZscore2 : numeric predictor; set to the value(s): 1.06834268357208.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
plot_smooth(gamm.model2a, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(f0Zscore2 = quantile(data.ai.mas$f0Zscore2, c(0.5), na.rm=T), durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.75))), col = "royalblue4", add = T, lwd = 4)Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; set to the value(s): -0.0524849620085245.
* durationZscore2 : numeric predictor; set to the value(s): 0.637773887350503.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
plot_smooth(gamm.model2a, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(f0Zscore2 = quantile(data.ai.mas$f0Zscore2, c(0.5), na.rm=T), durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.5))), col = "chartreuse4", add = T, lwd = 4)Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; set to the value(s): -0.0524849620085245.
* durationZscore2 : numeric predictor; set to the value(s): 0.0671853722597352.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
plot_smooth(gamm.model2a, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(f0Zscore2 = quantile(data.ai.mas$f0Zscore2, c(0.5), na.rm=T), durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.25))), col = "orange", add = T, lwd = 4)Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; set to the value(s): -0.0524849620085245.
* durationZscore2 : numeric predictor; set to the value(s): -0.449662795901817.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
plot_smooth(gamm.model2a, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(f0Zscore2 = quantile(data.ai.mas$f0Zscore2, c(0.5), na.rm=T), durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.15))), col = "red", add = T, lwd = 4)Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; set to the value(s): -0.0524849620085245.
* durationZscore2 : numeric predictor; set to the value(s): -0.644619456704238.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
legend("topright", legend=c("15%", "25%", "50%", "75%", "85%"),
col=c("red","orange", "chartreuse4", "royalblue4", "black"), lwd=4)#png("diffduration2.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_smooth(gamm.model2a, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(f0Zscore2 = quantile(data.ai.mas$f0Zscore2, c(0.5), na.rm=T), durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.85))), col = "black", lwd = 4, xlab = "Time (ms)", ylab = "F1 (Hz)", font.lab = 2, transform.view = function(measurement.no) measurement.no * duration0.85 * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1 + global_mean1, xaxt = "n", hide.label = T)Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; set to the value(s): -0.0524849620085245.
* durationZscore2 : numeric predictor; set to the value(s): 1.06834268357208.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model2a, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(f0Zscore2 = quantile(data.ai.mas$f0Zscore2, c(0.5), na.rm=T), durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.75))), col = "royalblue4", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * duration0.75 * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1 + global_mean1)Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; set to the value(s): -0.0524849620085245.
* durationZscore2 : numeric predictor; set to the value(s): 0.637773887350503.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model2a, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(f0Zscore2 = quantile(data.ai.mas$f0Zscore2, c(0.5), na.rm=T), durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.5))), col = "chartreuse4", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * duration0.5 * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1 + global_mean1)Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; set to the value(s): -0.0524849620085245.
* durationZscore2 : numeric predictor; set to the value(s): 0.0671853722597352.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model2a, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(f0Zscore2 = quantile(data.ai.mas$f0Zscore2, c(0.5), na.rm=T), durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.25))), col = "orange", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * duration0.25 * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1 + global_mean1)Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; set to the value(s): -0.0524849620085245.
* durationZscore2 : numeric predictor; set to the value(s): -0.449662795901817.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: X-values are transformed.
plot_smooth(gamm.model2a, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(f0Zscore2 = quantile(data.ai.mas$f0Zscore2, c(0.5), na.rm=T), durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.15))), col = "red", add = T, lwd = 4, transform.view = function(measurement.no) measurement.no * duration0.15 * 0.1, transform = function(f1Zscore2) f1Zscore2 * global_sd1 + global_mean1)Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; set to the value(s): -0.0524849620085245.
* durationZscore2 : numeric predictor; set to the value(s): -0.644619456704238.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: X-values are transformed.
legend("topright", legend=c("15%", "25%", "50%", "75%", "85%"),
col=c("red","orange", "chartreuse4", "royalblue4", "black"), lwd=4)# Generate the high resolution image for the paper
# output combined plot of 1000 dpi
png("pred2-diff-1c.png", width = 9, height = 7.5, units = "in", res = 1000)
layout(matrix(c(1, 2), nrow = 2, byrow = TRUE), heights = c(2, 1))
par(oma = c(4, 0, 1, 0), xaxs = "i", yaxs = "i")
x_range <- range(data.ai.mas$measurement.no, na.rm = TRUE)
par(mar = c(0.5, 4, 1.5, 2))
plot_diff2(gamm.model2a,
view = c("measurement.no", "durationZscore2"),
main = "",
comp = list(f0Zscore2 = quantile(data.ai.mas$f0Zscore2, c(0.8, 0.2), na.rm = TRUE)),
ylim = quantile(data.ai.mas$durationZscore2, c(0.05, 0.95), na.rm = TRUE),
xlim = x_range,
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no,
function(durationZscore2) durationZscore2 * global_sdd + global_meand),
sim.ci = FALSE,
show.diff = FALSE,
add.color.legend = FALSE,
rm.ranef = TRUE,
xlab = "", ylab = "Duration (ms)",
font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n",
color = mapcols_pastel, hide.label = TRUE)Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* durationZscore2 : numeric predictor; with 100 values ranging from -1.043110 to 1.889298.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
abline(h = (1.2 * global_sdd + global_meand), lty = 2, lwd = 2, col = "white")
par(mar = c(2, 4, 0.5, 2))
plot_diff(gamm.model2a,
view = "measurement.no",
comp = list(f0Zscore2 = quantile(data.ai.mas$f0Zscore2, c(0.8, 0.2), na.rm = TRUE)),
cond = list(durationZscore2 = 1.2),
rm.ranef = TRUE,
shade = FALSE,
main = "",
xlab = "", ylab = "Diff in F1 (Z)",
xlim = x_range,
xaxt = "n",
font.lab = 2, cex.lab = 1, cex.axis = 1, lwd = 2, hide.label = TRUE)Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* durationZscore2 : numeric predictor; set to the value(s): 1.2.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
Difference is not significant.
axis(1, at = tickvals, labels = ticknames, las = 1, cex.axis = 1)
mtext("Time (Normalized)", side = 1, outer = TRUE, line = 2.5, font = 2, cex = 1.3)
dev.off()null device
1
layout(matrix(c(1, 2), nrow = 2, byrow = TRUE), heights = c(2, 1))
par(oma = c(4, 0, 1, 0), xaxs = "i", yaxs = "i")
x_range <- range(data.ai.mas$measurement.no, na.rm = TRUE)
par(mar = c(0.5, 4, 1.5, 2))
plot_diff2(gamm.model2a,
view = c("measurement.no", "durationZscore2"),
main = "",
comp = list(f0Zscore2 = quantile(data.ai.mas$f0Zscore2, c(0.8, 0.2), na.rm = TRUE)),
ylim = quantile(data.ai.mas$durationZscore2, c(0.05, 0.95), na.rm = TRUE),
xlim = x_range,
transform.view = c(function(measurement.no) measurement.no,
function(durationZscore2) durationZscore2 * global_sdd + global_meand),
sim.ci = FALSE,
show.diff = FALSE,
add.color.legend = FALSE,
rm.ranef = TRUE,
xlab = "", ylab = "Duration (ms)",
font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n",
color = mapcols_pastel, hide.label = TRUE)Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* durationZscore2 : numeric predictor; with 30 values ranging from -1.043110 to 1.889298.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
par(mar = c(2, 4, 0.5, 2))
plot_diff(gamm.model2a,
view = "measurement.no",
comp = list(f0Zscore2 = quantile(data.ai.mas$f0Zscore2, c(0.8, 0.2), na.rm = TRUE)),
cond = list(durationZscore2 = 1.2),
rm.ranef = TRUE,
shade = FALSE,
main = "",
xlab = "", ylab = "Diff in F1 (Z)",
xlim = x_range,
xaxt = "n",
font.lab = 2, cex.lab = 1, cex.axis = 1, lwd = 2, hide.label = TRUE)Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* durationZscore2 : numeric predictor; set to the value(s): 1.2.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
Difference is not significant.
axis(1, at = tickvals, labels = ticknames, las = 1, cex.axis = 1)
mtext("Time (Normalized)", side = 1, outer = TRUE, line = 2.5, font = 2, cex = 1.3)# Modelling F2 ~ tone, with no autocorrelation
system.time(gamm.f0model.noAR <- bam(f0Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr"),
data=data.ai.mas, method="fREML", discrete = TRUE, nthreads = ncores)
)utilisateur système écoulé
0.479 0.012 0.124
# Modelling F2 ~ tone
# Final model with auto-correlation
system.time(gamm.f0model <- bam(f0Zscore2 ~ toneBis.ord +
# smooth
s(measurement.no, bs="cr") +
# smooth by factors
s(measurement.no, by=toneBis.ord, bs="cr"),
data=data.ai.mas, method="fREML", rho = r.gamm.f0model, AR.start = data.ai.mas$start, discrete = TRUE, nthreads = ncores)
)utilisateur système écoulé
0.287 0.005 0.042
#Plotting
### retested ordered factors
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2a, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.5))),
ylim = quantile(data.ai.mas$f0Zscore2, c(0.05,0.95), na.rm = T),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (Normalized)", ylab = "F0 (Z)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = "bw", xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.547736 to 1.651185.
* durationZscore2 : numeric predictor; set to the value(s): 0.0671853722597352.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
plot_smooth(gamm.f0model, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", ylim = quantile(data.ai.mas$f0Zscore2, c(0.05,0.95), na.rm = T),,
lwd = 4, xlab = "", ylab = "", xaxt = "n", font.lab = 2, add = T)Summary:
* toneBis.ord : factor; set to the value(s): 1.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* NOTE : No random effects in the model to cancel.
plot_smooth(gamm.f0model, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"),
col = "orange", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 2.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* NOTE : No random effects in the model to cancel.
plot_smooth(gamm.f0model, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"),
col = "chartreuse4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 3.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* NOTE : No random effects in the model to cancel.
plot_smooth(gamm.f0model, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"),
col = "royalblue4", add = T, lwd = 4)Summary:
* toneBis.ord : factor; set to the value(s): 4.
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* NOTE : No random effects in the model to cancel.
legend("bottomright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=2)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)#Plotting
### retested ordered factors
png("composition1.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2a, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.5))),
ylim = quantile(data.ai.mas$f0Zscore2, c(0.05,0.95), na.rm = T),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (Normalized)", ylab = "F0 (Z)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = "bw", xaxt = "n")
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
plot_smooth(gamm.f0model, view="measurement.no",
main = "", rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "1"), col = "red", ylim = quantile(data.ai.mas$f0Zscore2, c(0.05,0.95), na.rm = T),,
lwd = 4, xlab = "", ylab = "", xaxt = "n", font.lab = 2, add = T)
plot_smooth(gamm.f0model, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "2"),
col = "orange", add = T, lwd = 4)
plot_smooth(gamm.f0model, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "3"),
col = "chartreuse4", add = T, lwd = 4)
plot_smooth(gamm.f0model, view="measurement.no",
rug=F, rm.ranef = T, shade = F, cond = list(toneBis.ord = "4"),
col = "royalblue4", add = T, lwd = 4)
legend("bottomright", legend=c("Tone 1", "Tone 2", "Tone 3", "Tone 4"),
col=c("red","orange", "chartreuse4", "royalblue4"), lwd=2)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
dev.off()system.time(gamm.model2ate.noAR <- bam(f1Zscore2 ~
# te tensor
te(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.ai.mas, method="fREML", discrete = TRUE, nthreads = ncores)
)system.time(gamm.model2ate <- bam(f1Zscore2 ~
# te tensor
te(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.ai.mas, method="fREML", discrete = TRUE, nthreads = ncores, rho = r.gamm.model2ate, AR.start = data.ai.mas$start)
)
Family: gaussian
Link function: identity
Formula:
f1Zscore2 ~ te(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + s(word, bs = "re") + s(wordPos, bs = "re") +
s(wordLeftRightTone, bs = "re") + s(wordPos, measurement.no,
bs = "re") + s(wordPos, f0Zscore2, bs = "re") + s(wordPos,
durationZscore2, bs = "re") + s(wordLeftRightTone, measurement.no,
bs = "re") + s(wordLeftRightTone, f0Zscore2, bs = "re") +
s(wordLeftRightTone, durationZscore2, bs = "re") + s(word,
measurement.no, bs = "re") + s(word, f0Zscore2, bs = "re") +
s(word, durationZscore2, bs = "re") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speaker, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(measurement.no, speakerPos, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(durationZscore2, speakerPos, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(durationZscore2, speakerLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.05259 0.05057 -1.04 0.298
Approximate significance of smooth terms:
edf Ref.df F p-value
te(measurement.no,f0Zscore2,durationZscore2) 54.32 71.92 13.15 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.771 Deviance explained = 80.3%
fREML = 6009.3 Scale est. = 0.13463 n = 11029
Method: fREML Optimizer: perf chol
$grad
[1] 7.212009e-13 -2.522427e-13 -1.788791e-12 3.304024e-12 -1.247003e-12 -1.829648e-12
[7] 4.263256e-14 8.171241e-14 -5.151435e-14 6.394885e-13 -3.197442e-13 -3.215206e-13
[13] -6.288303e-13 3.552714e-15 -9.134682e-05 -9.023893e-13 -9.264209e-05 -1.367795e-13
[19] -9.264209e-05 -4.014566e-13 -9.264209e-05 1.172396e-13 5.173639e-14 0.000000e+00
[25] 1.061373e-13 1.776357e-14 4.130030e-14 -1.563194e-13 3.774758e-14 3.979039e-13
[31] 3.730349e-14 -1.385558e-13 -8.393286e-14 1.455192e-11
$hess
[,1] [,2] [,3] [,4] [,5] [,6]
5.188001e+00 7.070166e-02 1.115972e-01 -1.147504e-02 9.895278e-03 3.525500e-03
7.070166e-02 9.012753e-01 4.572425e-01 8.988453e-02 2.261362e-02 3.699769e-02
1.115972e-01 4.572425e-01 1.850239e+00 1.608275e-01 5.109433e-02 2.520025e-02
-1.147504e-02 8.988453e-02 1.608275e-01 1.946286e+01 4.299996e+00 3.830146e+00
9.895278e-03 2.261362e-02 5.109433e-02 4.299996e+00 9.064811e+00 7.070647e-01
3.525500e-03 3.699769e-02 2.520025e-02 3.830146e+00 7.070647e-01 7.531835e+00
1.396767e-02 1.015448e-01 9.147414e-02 -7.443352e-01 6.573249e-01 1.191398e-01
-1.567791e-03 5.247568e-02 6.785587e-03 -7.783780e-02 4.203683e-01 1.004370e-01
-2.376092e-03 -1.975131e-02 1.076698e-03 8.104132e-01 2.859538e-01 3.205752e-01
4.822148e-04 1.540589e-01 2.596237e-01 -3.135857e+00 -6.797270e-01 -2.317508e+00
1.953989e-02 1.173771e-01 1.956216e-01 1.129581e-02 -8.133214e-02 -3.831317e-01
9.154741e-03 -3.501889e-02 -6.379211e-02 5.933564e-01 2.865775e-01 6.041066e-01
7.658543e-04 2.644431e-02 7.693600e-02 -1.316617e+00 -2.380616e-01 -2.725343e-01
2.047425e-03 3.872940e-03 9.241259e-03 8.669250e-03 5.948245e-03 1.468515e-02
6.492905e-07 7.584493e-07 1.101168e-06 5.555260e-05 2.305081e-05 2.587461e-05
8.540463e-02 1.604533e-02 6.317508e-02 -7.677012e-02 -3.605730e-02 -2.156512e-02
9.413137e-07 2.165759e-06 1.267550e-05 -1.246160e-06 4.798679e-06 -2.154672e-05
7.555759e-04 2.421823e-03 8.521740e-03 1.031988e-01 1.876452e-02 3.568459e-02
9.413137e-07 2.165759e-06 1.267550e-05 -1.246160e-06 4.798679e-06 -2.154672e-05
1.558590e-02 -1.113138e-01 1.182997e-01 4.005980e-02 -1.391299e-02 -4.520616e-02
9.413138e-07 2.165759e-06 1.267550e-05 -1.246160e-06 4.798679e-06 -2.154672e-05
1.103605e-02 -2.607238e-02 -1.440185e-02 3.551112e-01 1.816060e-01 5.029666e-02
1.204923e-03 -3.165195e-03 -1.101602e-02 -4.121962e-02 -7.968617e-03 -1.805989e-02
1.112656e-02 3.392380e-02 2.834617e-02 5.944516e-01 3.532166e-01 5.319058e-01
1.204923e-03 -3.165195e-03 -1.101602e-02 -4.121962e-02 -7.968617e-03 -1.805989e-02
1.057317e-02 -2.812451e-02 -1.271693e-02 1.915228e-01 -2.517857e-01 7.876653e-02
1.204923e-03 -3.165195e-03 -1.101602e-02 -4.121962e-02 -7.968616e-03 -1.805989e-02
4.483139e-02 1.891545e-01 1.770829e-02 1.195657e-01 -5.655524e-02 2.430439e-01
7.039883e-04 1.909300e-03 8.748746e-03 1.703776e-02 7.875045e-03 -6.890274e-02
[,7] [,8] [,9] [,10] [,11] [,12]
1.396767e-02 -1.567791e-03 -2.376092e-03 4.822148e-04 1.953989e-02 9.154741e-03
1.015448e-01 5.247568e-02 -1.975131e-02 1.540589e-01 1.173771e-01 -3.501889e-02
9.147414e-02 6.785587e-03 1.076698e-03 2.596237e-01 1.956216e-01 -6.379211e-02
-7.443352e-01 -7.783780e-02 8.104132e-01 -3.135857e+00 1.129581e-02 5.933564e-01
6.573249e-01 4.203683e-01 2.859538e-01 -6.797270e-01 -8.133214e-02 2.865775e-01
1.191398e-01 1.004370e-01 3.205752e-01 -2.317508e+00 -3.831317e-01 6.041066e-01
1.484122e+01 4.635109e-01 -3.397288e-01 9.540342e+00 9.281281e-02 -3.065428e-01
4.635109e-01 7.541022e+00 1.351556e-01 1.943293e-01 3.270023e+00 -2.878651e-02
-3.397288e-01 1.351556e-01 3.584680e+00 -4.106119e-01 -2.416990e-01 1.726895e+00
9.540342e+00 1.943293e-01 -4.106119e-01 4.315220e+01 -2.123477e-01 -3.864110e-01
9.281281e-02 3.270023e+00 -2.416990e-01 -2.123477e-01 7.852431e+00 -3.200757e-01
-3.065428e-01 -2.878651e-02 1.726895e+00 -3.864110e-01 -3.200757e-01 3.268123e+00
2.912164e+00 -2.732735e-02 -1.033708e-01 7.687327e+00 1.876938e-01 -1.014930e-01
1.550674e-02 4.179317e-01 1.986650e-02 3.003052e-02 4.907111e-01 -1.934225e-02
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[ getOption("max.print") est atteint -- 5 lignes omises ]
Model rank = 8830 / 8830
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
te(measurement.no,f0Zscore2,durationZscore2) 4.79e+02 5.43e+01 1.01 0.83
s(word) 2.09e+02 8.45e+01 NA NA
s(wordPos) 3.31e+02 5.85e+01 NA NA
s(wordLeftRightTone) 3.10e+02 5.33e+01 NA NA
s(measurement.no,wordPos) 3.31e+02 9.09e+01 NA NA
s(f0Zscore2,wordPos) 3.31e+02 5.43e+01 NA NA
s(durationZscore2,wordPos) 3.31e+02 2.77e+01 NA NA
s(measurement.no,wordLeftRightTone) 3.10e+02 1.66e+02 NA NA
s(f0Zscore2,wordLeftRightTone) 3.10e+02 7.97e+01 NA NA
s(durationZscore2,wordLeftRightTone) 3.10e+02 3.01e+01 NA NA
s(measurement.no,word) 2.09e+02 3.70e+01 NA NA
s(f0Zscore2,word) 2.09e+02 5.10e+00 NA NA
s(durationZscore2,word) 2.09e+02 2.01e-03 NA NA
s(measurement.no,speaker) 1.00e+02 7.15e+01 1.00 0.54
s(durationZscore2,speaker) 3.00e+02 8.66e+00 0.98 0.12
s(f0Zscore2,speaker) 1.00e+02 4.00e+01 1.01 0.64
s(measurement.no,speakerPos) 3.00e+02 4.76e+01 1.00 0.45
s(durationZscore2,speakerPos) 9.00e+02 1.43e+02 0.98 0.21
s(f0Zscore2,speakerPos) 3.00e+02 6.50e+01 1.01 0.64
s(measurement.no,speakerLeftRightTone) 5.90e+02 1.15e+02 1.00 0.51
s(durationZscore2,speakerLeftRightTone) 1.77e+03 2.52e+02 0.98 0.15
s(f0Zscore2,speakerLeftRightTone) 5.90e+02 5.63e+01 1.01 0.72
system.time(gamm.model2b.noAR <- bam(f1Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.ai.fem, method="fREML", discrete = TRUE, nthreads = ncores)
)# Auto-regressive model
system.time(gamm.model2b <- bam(f1Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.ai.fem, method="fREML", discrete = TRUE, nthreads = ncores, rho = r.gamm.model2b, AR.start = data.ai.fem$start)
)
Family: gaussian
Link function: identity
Formula:
f1Zscore2 ~ s(measurement.no, bs = "cr", k = 10) + s(f0Zscore2,
bs = "cr", k = 10) + s(durationZscore2, bs = "cr", k = 30) +
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + ti(measurement.no, durationZscore2,
bs = "cr", k = c(5, 12)) + ti(measurement.no, f0Zscore2,
bs = "cr", k = c(5, 8)) + ti(f0Zscore2, durationZscore2,
bs = "cr", k = c(8, 12)) + s(word, bs = "re") + s(wordPos,
bs = "re") + s(wordLeftRightTone, bs = "re") + s(wordPos,
measurement.no, bs = "re") + s(wordPos, f0Zscore2, bs = "re") +
s(wordPos, durationZscore2, bs = "re") + s(wordLeftRightTone,
measurement.no, bs = "re") + s(wordLeftRightTone, f0Zscore2,
bs = "re") + s(wordLeftRightTone, durationZscore2, bs = "re") +
s(word, measurement.no, bs = "re") + s(word, f0Zscore2, bs = "re") +
s(word, durationZscore2, bs = "re") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speaker, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(measurement.no, speakerPos, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(durationZscore2, speakerPos, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(durationZscore2, speakerLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.22118 0.05384 4.108 4.02e-05 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 8.063 8.233 128.643 <2e-16 ***
s(f0Zscore2) 3.926 4.392 3.229 0.0101 *
s(durationZscore2) 1.000 1.000 0.217 0.6418
ti(measurement.no,f0Zscore2,durationZscore2) 34.234 49.415 1.167 0.2020
ti(measurement.no,durationZscore2) 11.876 14.803 10.933 <2e-16 ***
ti(measurement.no,f0Zscore2) 16.710 19.949 9.018 <2e-16 ***
ti(f0Zscore2,durationZscore2) 7.521 10.185 0.421 0.9402
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.821 Deviance explained = 84.6%
fREML = 6042.4 Scale est. = 0.15276 n = 10275
Method: fREML Optimizer: perf chol
$grad
[1] -1.154632e-13 8.200107e-13 -6.545912e-05 6.128431e-14 7.949197e-14 3.286260e-14
[7] -6.084022e-14 4.307665e-14 -7.975842e-13 -1.813660e-12 -2.731149e-14 -1.620926e-14
[13] -4.547474e-13 -1.350031e-13 -4.440892e-14 -7.815970e-14 2.220446e-13 6.394885e-13
[19] 1.200817e-12 -5.950795e-14 1.776357e-14 -4.263256e-13 1.030287e-13 -4.178096e-05
[25] 4.156675e-13 -4.280935e-05 -8.402220e-05 -4.280935e-05 -2.415845e-13 -4.280935e-05
[31] -1.350031e-13 -4.307665e-14 -3.410605e-13 -4.063416e-14 1.278977e-13 -3.375078e-14
[37] 5.684342e-14 -1.114664e-13 -1.421085e-13 1.110223e-14 2.700062e-13 1.021405e-13
[43] -2.546585e-11
$hess
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-4.949194e-02 -4.384994e-04 4.147029e-02 -4.384994e-04 1.852035e-02 -4.384994e-04
-4.730307e-02 2.714356e-04 2.192485e-02 2.714356e-04 -2.855575e-02 2.714356e-04
-5.468679e-03 6.848355e-03 1.453524e-03 6.848355e-03 1.193266e-01 6.848355e-03
-1.771742e-02 5.252320e-03 9.797827e-02 5.252320e-03 4.410153e-02 5.252320e-03
1.247973e-02 -1.151208e-03 1.686217e-01 -1.151208e-03 -2.258599e-02 -1.151208e-03
1.291672e-01 6.876345e-02 1.242513e+00 6.876345e-02 1.028768e-01 6.876345e-02
3.707421e-02 -7.060139e-03 1.807025e-01 -7.060139e-03 -4.069938e-01 -7.060139e-03
-3.584898e-03 7.647388e-03 -2.576808e-02 7.647388e-03 -1.274355e-03 7.647388e-03
1.358725e-01 -9.622110e-03 -9.981120e-02 -9.622110e-03 -2.260521e-01 -9.622110e-03
-9.396728e-03 1.458265e-02 2.164233e-01 1.458265e-02 1.858056e-01 1.458265e-02
1.211209e-01 8.944856e-02 1.586626e+00 8.944856e-02 1.447643e-01 8.944856e-02
4.141820e-02 -2.298850e-02 -2.146522e-01 -2.298850e-02 3.737647e-01 -2.298850e-02
-2.826044e-02 -2.842588e-06 1.873720e-02 -2.842588e-06 1.225322e-01 -2.842588e-06
2.836610e-02 2.668043e-02 8.316054e-01 2.668043e-02 -3.552386e-02 2.668043e-02
3.900724e-02 -1.605477e-02 -6.881064e-02 -1.605477e-02 2.453334e-01 -1.605477e-02
-1.690925e-01 -3.207616e-02 -6.146330e-01 -3.207616e-02 2.494164e-01 -3.207616e-02
[,37] [,38] [,39] [,40] [,41] [,42]
1.577319e-02 -2.751835e-04 -1.000108e-03 -2.751835e-04 -3.434716e-03 -2.751835e-04
-1.259132e-02 -5.690304e-03 -2.238120e-02 -5.690304e-03 -1.188775e-02 -5.690304e-03
-2.373815e-06 1.029718e-07 -1.671917e-05 1.029718e-07 -2.918244e-06 1.029718e-07
8.362720e-02 2.313893e-03 6.035128e-02 2.313893e-03 2.122411e-02 2.313893e-03
9.492845e-02 7.694474e-03 1.255966e-01 7.694474e-03 4.262244e-03 7.694474e-03
1.187391e-01 1.153349e-02 -5.436739e-02 1.153349e-02 1.669989e-02 1.153349e-02
-3.412461e-03 1.576106e-03 7.670558e-03 1.576106e-03 9.425288e-03 1.576106e-03
6.458537e-03 4.180304e-05 2.908242e-02 4.180304e-05 5.071690e-02 4.180304e-05
8.876498e-02 -2.081839e-03 4.936132e-02 -2.081839e-03 -3.091464e-02 -2.081839e-03
8.792320e-02 4.636077e-03 9.053258e-02 4.636077e-03 2.238453e-02 4.636077e-03
-6.303788e-02 7.740886e-03 4.573763e-02 7.740886e-03 4.939773e-02 7.740886e-03
-1.993041e-02 4.651129e-03 9.667978e-03 4.651129e-03 4.201227e-02 4.651129e-03
1.409098e-01 4.241670e-02 1.393120e+00 4.241670e-02 2.900452e-01 4.241670e-02
2.332679e-01 -2.153071e-02 5.126337e-01 -2.153071e-02 6.951312e-02 -2.153071e-02
-1.142538e-02 1.509765e-02 8.690495e-02 1.509765e-02 -7.460638e-02 1.509765e-02
6.108820e-01 -1.268221e-02 3.518212e-01 -1.268221e-02 8.051495e-02 -1.268221e-02
2.640660e-01 -2.724879e-03 2.692114e-01 -2.724879e-03 8.715751e-02 -2.724879e-03
1.244480e-01 7.084991e-02 9.191380e-01 7.084992e-02 3.940943e-01 7.084992e-02
2.462195e+00 1.194610e-01 -2.940413e-01 1.194610e-01 7.824849e-01 1.194610e-01
1.152969e-01 3.346237e-02 1.493990e-01 3.346237e-02 -1.479669e-01 3.346237e-02
1.052722e-01 4.979546e-02 7.842352e-01 4.979546e-02 -2.052034e-03 4.979546e-02
4.932294e-01 -7.583424e-03 -1.134310e-01 -7.583424e-03 1.580448e-01 -7.583424e-03
1.012813e-01 5.779883e-02 7.477003e-02 5.779883e-02 4.934622e-01 5.779883e-02
[,43]
-3.531617e+00
-1.462751e+00
-3.644364e-05
-5.332093e+00
-3.567155e+00
-7.717775e+00
-1.801526e+00
-3.636457e+00
-3.366687e+00
-4.488497e+00
-1.522955e+00
-1.737318e+00
-5.553566e+01
-1.945388e+01
-2.557287e+00
-3.923389e+01
-1.180842e+01
-3.540107e+01
-5.825920e+01
-6.572260e+00
-1.102390e+01
-2.883684e+01
-2.579244e+01
[ getOption("max.print") est atteint -- 20 lignes omises ]
Model rank = 8663 / 8663
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00e+00 8.06e+00 0.99 0.225
s(f0Zscore2) 9.00e+00 3.93e+00 1.04 1.000
s(durationZscore2) 2.90e+01 1.00e+00 0.98 0.080 .
ti(measurement.no,f0Zscore2,durationZscore2) 3.08e+02 3.42e+01 1.00 0.485
ti(measurement.no,durationZscore2) 4.40e+01 1.19e+01 1.03 0.990
ti(measurement.no,f0Zscore2) 2.80e+01 1.67e+01 1.01 0.660
ti(f0Zscore2,durationZscore2) 7.70e+01 7.52e+00 0.99 0.120
s(word) 2.03e+02 1.11e+02 NA NA
s(wordPos) 3.09e+02 3.89e+01 NA NA
s(wordLeftRightTone) 2.90e+02 5.11e+00 NA NA
s(measurement.no,wordPos) 3.09e+02 7.85e+01 NA NA
s(f0Zscore2,wordPos) 3.09e+02 2.36e+01 NA NA
s(durationZscore2,wordPos) 3.09e+02 7.08e+01 NA NA
s(measurement.no,wordLeftRightTone) 2.90e+02 1.17e+02 NA NA
s(f0Zscore2,wordLeftRightTone) 2.90e+02 1.31e+01 NA NA
s(durationZscore2,wordLeftRightTone) 2.90e+02 2.20e+01 NA NA
s(measurement.no,word) 2.03e+02 5.77e+01 NA NA
s(f0Zscore2,word) 2.03e+02 5.16e+01 NA NA
s(durationZscore2,word) 2.03e+02 3.98e-03 NA NA
s(measurement.no,speaker) 1.00e+02 5.77e+01 0.99 0.190
s(durationZscore2,speaker) 3.00e+02 8.78e-04 0.98 0.095 .
s(f0Zscore2,speaker) 1.00e+02 3.48e+01 1.04 0.995
s(measurement.no,speakerPos) 3.00e+02 7.22e+01 0.99 0.190
s(durationZscore2,speakerPos) 9.00e+02 1.67e+02 0.98 0.080 .
s(f0Zscore2,speakerPos) 3.00e+02 6.79e+01 1.04 1.000
s(measurement.no,speakerLeftRightTone) 5.90e+02 1.13e+02 0.99 0.185
s(durationZscore2,speakerLeftRightTone) 1.77e+03 1.66e+02 0.98 0.095 .
s(f0Zscore2,speakerLeftRightTone) 5.90e+02 9.40e+01 1.04 1.000
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
duration0.25f = quantile(data.ai.fem$durationZscore2, c(0.25)) * global_sddf + global_meandf
duration0.5f = quantile(data.ai.fem$durationZscore2, c(0.5)) * global_sddf + global_meandf
duration0.75f = quantile(data.ai.fem$durationZscore2, c(0.75)) * global_sddf + global_meandf# 3D plotting
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2b, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.fem$durationZscore2, c(0.25))),
ylim = quantile(data.ai.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.25f * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0f + global_mean0f),
transform = function(f1Zscore2) f1Zscore2 * global_sd1f + global_mean1f,
zlim = c(500,1000),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.243937 to 1.329686.
* durationZscore2 : numeric predictor; set to the value(s): -0.627777955022104.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(500,1000), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))fvisgam(gamm.model2b, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2. = quantile(data.ai.fem$durationZscore2, c(0.5))),
ylim = quantile(data.ai.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.5f * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0f + global_mean0f),
transform = function(f1Zscore2) f1Zscore2 * global_sd1f + global_mean1f,
zlim = c(500,1000),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.243937 to 1.329686.
* durationZscore2 : numeric predictor; set to the value(s): -0.0952338520379409.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(500,1000), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))fvisgam(gamm.model2b, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.fem$durationZscore2, c(0.75))),
ylim = quantile(data.ai.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.75f * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0f + global_mean0f),
transform = function(f1Zscore2) f1Zscore2 * global_sd1f + global_mean1f,
zlim = c(500,1000),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.243937 to 1.329686.
* durationZscore2 : numeric predictor; set to the value(s): 0.525044865601105.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(500,1000), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_diff2(gamm.model2b, view=c("measurement.no","durationZscore2"),
main = "",
comp = list(f0Zscore2 = quantile(data.ai.fem$f0Zscore2, c(0.8,0.2), na.rm = T)),
ylim = quantile(data.ai.fem$durationZscore2, c(0.05,0.95), na.rm = T),
transform.view = c(function(measurement.no) measurement.no, function(durationZscore2) durationZscore2 * global_sddf + global_meandf),
#zlim = c(-0.5,0.5),
print.summary = TRUE,
sim.ci = F,
show.diff = F,
#color = "heat",
alpha.diff = 0.5,
#plot.type = "perp",
#n.grid =300,
add.color.legend = FALSE, rm.ranef = TRUE,
xlab = "Time (Normalized)", ylab = "Duration (ms)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, hide.label = T)Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* durationZscore2 : numeric predictor; with 30 values ranging from -1.397262 to 1.834229.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
#gradientLegend(valRange=c(-50,20), length=.5, pos=.75, depth = 0.02, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)# 3D plotting
png("pred2-4.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2b, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.fem$durationZscore2, c(0.25))),
ylim = quantile(data.ai.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.25f * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0f + global_mean0f),
transform = function(f1Zscore2) f1Zscore2 * global_sd1f + global_mean1f,
zlim = c(500,1000),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.243937 to 1.329686.
* durationZscore2 : numeric predictor; set to the value(s): -0.627777955022104.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(500,1000), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2b, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2. = quantile(data.ai.fem$durationZscore2, c(0.5))),
ylim = quantile(data.ai.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.5f * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0f + global_mean0f),
transform = function(f1Zscore2) f1Zscore2 * global_sd1f + global_mean1f,
zlim = c(500,1000),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.243937 to 1.329686.
* durationZscore2 : numeric predictor; set to the value(s): -0.0952338520379409.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(500,1000), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2b, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.fem$durationZscore2, c(0.75))),
ylim = quantile(data.ai.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.75f * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0f + global_mean0f),
transform = function(f1Zscore2) f1Zscore2 * global_sd1f + global_mean1f,
zlim = c(500,1000),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.243937 to 1.329686.
* durationZscore2 : numeric predictor; set to the value(s): 0.525044865601105.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(500,1000), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
png("pred2-diff-2.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_diff2(gamm.model2b, view=c("measurement.no","durationZscore2"),
main = "",
comp = list(f0Zscore2 = quantile(data.ai.fem$f0Zscore2, c(0.8,0.2), na.rm = T)),
ylim = quantile(data.ai.fem$durationZscore2, c(0.05,0.95), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no, function(durationZscore2) durationZscore2 * global_sddf + global_meandf),
print.summary = TRUE,
sim.ci = F,
show.diff = F,
#color = "heat",
alpha.diff = 0.5,
#plot.type = "perp",
#n.grid =300,
add.color.legend = FALSE, rm.ranef = TRUE,
xlab = "Time (Normalized)", ylab = "Duration (ms)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, hide.label = T)Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* durationZscore2 : numeric predictor; with 100 values ranging from -1.397262 to 1.834229.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
#gradientLegend(valRange=c(-50,20), length=.5, pos=.75, depth = 0.02, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
#abline(h = (1.2 * global_sdd1 + global_meand1), lty=2,lwd=2, col = "white")
dev.off()null device
1
system.time(gamm.model2c.noAR <- bam(f1Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.au.mas, method="fREML", discrete = TRUE, nthreads = ncores)
)# Auto-regressive model
system.time(gamm.model2c <- bam(f1Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.au.mas, method="fREML", discrete = TRUE, nthreads = ncores, rho = r.gamm.model2c, AR.start = data.au.mas$start)
)
Family: gaussian
Link function: identity
Formula:
f1Zscore2 ~ s(measurement.no, bs = "cr", k = 10) + s(f0Zscore2,
bs = "cr", k = 10) + s(durationZscore2, bs = "cr", k = 30) +
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + ti(measurement.no, durationZscore2,
bs = "cr", k = c(5, 12)) + ti(measurement.no, f0Zscore2,
bs = "cr", k = c(5, 8)) + ti(f0Zscore2, durationZscore2,
bs = "cr", k = c(8, 12)) + s(word, bs = "re") + s(wordPos,
bs = "re") + s(wordLeftRightTone, bs = "re") + s(wordPos,
measurement.no, bs = "re") + s(wordPos, f0Zscore2, bs = "re") +
s(wordPos, durationZscore2, bs = "re") + s(wordLeftRightTone,
measurement.no, bs = "re") + s(wordLeftRightTone, f0Zscore2,
bs = "re") + s(wordLeftRightTone, durationZscore2, bs = "re") +
s(word, measurement.no, bs = "re") + s(word, f0Zscore2, bs = "re") +
s(word, durationZscore2, bs = "re") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speaker, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(measurement.no, speakerPos, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(durationZscore2, speakerPos, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(durationZscore2, speakerLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.11603 0.05027 -2.308 0.021 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 7.877 8.200 75.621 <2e-16 ***
s(f0Zscore2) 1.000 1.000 2.632 0.105
s(durationZscore2) 1.000 1.000 0.081 0.776
ti(measurement.no,f0Zscore2,durationZscore2) 77.986 103.329 1.889 <2e-16 ***
ti(measurement.no,durationZscore2) 18.835 21.871 3.609 <2e-16 ***
ti(measurement.no,f0Zscore2) 1.001 1.002 0.710 0.400
ti(f0Zscore2,durationZscore2) 12.782 16.359 1.115 0.294
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.704 Deviance explained = 75.3%
fREML = 9240 Scale est. = 0.27859 n = 9522
Method: fREML Optimizer: perf chol
$grad
[1] 1.509903e-14 -4.421812e-05 -5.173769e-05 -5.329071e-15 2.913225e-13 5.719869e-13
[7] -6.661338e-14 -1.625367e-13 -4.137722e-05 -7.430545e-05 -2.797762e-14 8.881784e-16
[13] -3.019807e-13 4.263256e-14 8.810730e-13 -1.989520e-13 1.065814e-13 -2.806644e-13
[19] 1.421085e-14 -7.744916e-13 3.694822e-13 6.075140e-13 -5.943035e-05 8.615331e-14
[25] -3.552714e-13 -4.513057e-14 1.332268e-13 2.009504e-14 9.592327e-14 -5.551115e-15
[31] -7.105427e-15 -2.216005e-13 -6.863694e-05 1.048051e-13 -2.096101e-13 3.108624e-14
[37] -7.105427e-14 8.659740e-15 -1.563194e-13 -2.642331e-14 -5.826450e-13 -4.507505e-14
[43] 6.366463e-12
$hess
[,1] [,2] [,3] [,4] [,5] [,6]
3.436732e+00 1.146967e-07 2.882443e-07 1.981049e-02 5.047585e-03 -8.700809e-03
1.146967e-07 4.421468e-05 -1.659474e-11 -5.374701e-07 1.115960e-06 -7.118915e-07
2.882443e-07 -1.659474e-11 5.174411e-05 6.824430e-06 -4.923589e-06 -6.712126e-06
1.981049e-02 -5.374701e-07 6.824430e-06 3.417803e+00 3.066756e-02 5.502142e-01
5.047585e-03 1.115960e-06 -4.923589e-06 3.066756e-02 2.327217e+00 7.406141e-01
-8.700809e-03 -7.118915e-07 -6.712126e-06 5.502142e-01 7.406141e-01 3.237080e+00
-1.286566e-03 2.507969e-08 4.498085e-07 -4.576287e-03 1.492604e-03 -8.137149e-04
8.758973e-03 6.527397e-08 -4.706856e-06 1.217636e-02 7.569456e-01 3.032156e-01
-5.862305e-06 -2.051877e-10 -2.690992e-11 2.381049e-05 -2.370795e-06 5.321780e-06
-2.365183e-06 -5.425586e-10 2.566724e-10 6.576532e-06 -3.111268e-06 -9.304259e-06
-2.036204e-03 -1.843609e-07 -5.810039e-06 8.184781e-03 -1.453347e-01 5.335916e-02
-1.605283e-03 7.029070e-08 -6.856684e-06 1.235986e-02 -2.783766e-02 2.790303e-02
-5.044123e-03 8.504241e-07 3.420854e-06 -7.902620e-03 4.143748e-03 6.607474e-02
-5.170657e-03 1.260296e-07 1.170420e-06 -1.010465e-02 7.225012e-02 2.643432e-02
-3.765831e-03 7.069552e-07 7.810375e-07 -5.106029e-02 4.161716e-02 1.450322e-01
9.824810e-03 -1.140226e-06 1.620483e-06 -7.117713e-03 3.114254e-02 1.858161e-01
7.636842e-04 -7.422579e-07 -1.097526e-06 -1.301220e-02 -8.448967e-03 -3.785656e-02
1.792185e-03 -3.364212e-07 3.255858e-07 -1.642050e-03 -3.348531e-02 9.556300e-03
3.281171e-02 -2.462839e-06 2.262868e-05 1.455296e-01 2.173006e-01 2.586209e-01
5.950808e-03 -4.126734e-07 1.206912e-06 1.286570e-01 1.635486e-01 1.661803e-01
-2.423714e-03 -6.516604e-07 1.517338e-05 -4.596442e-03 -2.228014e-02 -5.952660e-03
1.279447e-02 -8.036689e-07 1.176031e-05 1.845857e-02 7.865775e-03 1.095766e-01
2.154697e-07 -4.678510e-11 3.379692e-10 5.635054e-07 -9.493168e-07 9.339618e-07
[,7] [,8] [,9] [,10] [,11] [,12]
-1.286566e-03 8.758973e-03 -5.862305e-06 -2.365183e-06 -2.036204e-03 -1.605283e-03
2.507969e-08 6.527397e-08 -2.051877e-10 -5.425586e-10 -1.843609e-07 7.029070e-08
4.498085e-07 -4.706856e-06 -2.690992e-11 2.566724e-10 -5.810039e-06 -6.856684e-06
-4.576287e-03 1.217636e-02 2.381049e-05 6.576532e-06 8.184781e-03 1.235986e-02
1.492604e-03 7.569456e-01 -2.370795e-06 -3.111268e-06 -1.453347e-01 -2.783766e-02
-8.137149e-04 3.032156e-01 5.321780e-06 -9.304259e-06 5.335916e-02 2.790303e-02
1.235990e+00 2.098012e-02 -1.463403e-06 2.370865e-07 3.383424e-03 1.318383e-03
2.098012e-02 2.460554e+00 4.547433e-06 4.118789e-06 3.683270e-02 -1.790341e-02
-1.463403e-06 4.547433e-06 1.825315e-05 2.313124e-05 -2.393962e-06 -1.923176e-06
2.370865e-07 4.118789e-06 2.313124e-05 5.115512e-05 -9.165367e-08 -1.135160e-06
3.383424e-03 3.683270e-02 -2.393962e-06 -9.165367e-08 3.336908e-01 2.742291e-02
1.318383e-03 -1.790341e-02 -1.923176e-06 -1.135160e-06 2.742291e-02 5.975948e-01
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[ getOption("max.print") est atteint -- 20 lignes omises ]
Model rank = 10417 / 10417
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00e+00 7.88e+00 1.03 0.97
s(f0Zscore2) 9.00e+00 1.00e+00 1.00 0.44
s(durationZscore2) 2.90e+01 1.00e+00 1.01 0.69
ti(measurement.no,f0Zscore2,durationZscore2) 3.08e+02 7.80e+01 1.00 0.52
ti(measurement.no,durationZscore2) 4.40e+01 1.88e+01 1.02 0.89
ti(measurement.no,f0Zscore2) 2.80e+01 1.00e+00 1.00 0.58
ti(f0Zscore2,durationZscore2) 7.70e+01 1.28e+01 1.02 0.82
s(word) 3.19e+02 4.85e+01 NA NA
s(wordPos) 4.66e+02 4.85e+01 NA NA
s(wordLeftRightTone) 4.43e+02 1.49e+02 NA NA
s(measurement.no,wordPos) 4.66e+02 1.02e+02 NA NA
s(f0Zscore2,wordPos) 4.66e+02 6.18e+01 NA NA
s(durationZscore2,wordPos) 4.66e+02 2.30e+01 NA NA
s(measurement.no,wordLeftRightTone) 4.43e+02 1.89e+02 NA NA
s(f0Zscore2,wordLeftRightTone) 4.43e+02 8.71e+01 NA NA
s(durationZscore2,wordLeftRightTone) 4.43e+02 5.18e+01 NA NA
s(measurement.no,word) 3.19e+02 5.19e+01 NA NA
s(f0Zscore2,word) 3.19e+02 1.60e-03 NA NA
s(durationZscore2,word) 3.19e+02 4.88e+00 NA NA
s(measurement.no,speaker) 1.00e+02 3.70e+01 1.03 0.98
s(durationZscore2,speaker) 3.00e+02 3.19e+01 1.01 0.71
s(f0Zscore2,speaker) 1.00e+02 3.83e+01 1.00 0.39
s(measurement.no,speakerPos) 3.00e+02 6.18e+01 1.03 0.99
s(durationZscore2,speakerPos) 9.00e+02 4.10e+00 1.01 0.71
s(f0Zscore2,speakerPos) 3.00e+02 4.09e+01 1.00 0.43
s(measurement.no,speakerLeftRightTone) 6.00e+02 1.55e+02 1.03 0.97
s(durationZscore2,speakerLeftRightTone) 1.80e+03 1.64e+02 1.01 0.68
s(f0Zscore2,speakerLeftRightTone) 6.00e+02 1.12e+02 1.00 0.43
duration0.25au = quantile(data.au.mas$durationZscore2, c(0.25)) * global_sddau + global_meandau
duration0.5au = quantile(data.au.mas$durationZscore2, c(0.5)) * global_sddau + global_meandau
duration0.75au = quantile(data.au.mas$durationZscore2, c(0.75)) * global_sddau + global_meandau# 3D plotting
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2c, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.au.mas$durationZscore2, c(0.25))),
ylim = quantile(data.au.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.25au * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0au + global_mean0au),
transform = function(f1Zscore2) f1Zscore2 * global_sd1au + global_mean1au,
zlim = c(490,720),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.253736 to 1.355745.
* durationZscore2 : numeric predictor; set to the value(s): -0.680380067515762.
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(490,720), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))fvisgam(gamm.model2c, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2. = quantile(data.au.mas$durationZscore2, c(0.5))),
ylim = quantile(data.au.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.5au * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0au + global_mean0au),
transform = function(f1Zscore2) f1Zscore2 * global_sd1au + global_mean1au,
zlim = c(490,720),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.253736 to 1.355745.
* durationZscore2 : numeric predictor; set to the value(s): -0.0990769355270091.
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(490,720), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))fvisgam(gamm.model2c, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.au.mas$durationZscore2, c(0.75))),
ylim = quantile(data.au.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.75au * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0au + global_mean0au),
transform = function(f1Zscore2) f1Zscore2 * global_sd1au + global_mean1au,
zlim = c(490,720),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.253736 to 1.355745.
* durationZscore2 : numeric predictor; set to the value(s): 0.530017553918074.
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(490,720), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_diff2(gamm.model2c, view=c("measurement.no","durationZscore2"),
main = "",
comp = list(f0Zscore2 = quantile(data.au.mas$f0Zscore2, c(0.8,0.2), na.rm = T)),
ylim = quantile(data.au.mas$durationZscore2, c(0.05,0.95), na.rm = T),
transform.view = c(function(measurement.no) measurement.no, function(durationZscore2) durationZscore2 * global_sddau + global_meandau),
#zlim = c(-0.5,0.5),
print.summary = TRUE,
sim.ci = F,
show.diff = F,
#color = "heat",
alpha.diff = 0.5,
#plot.type = "perp",
#n.grid =300,
add.color.legend = FALSE, rm.ranef = TRUE,
xlab = "Time (Normalized)", ylab = "Duration (ms)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, hide.label = T)Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* durationZscore2 : numeric predictor; with 30 values ranging from -1.441948 to 1.867158.
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
#gradientLegend(valRange=c(-50,20), length=.5, pos=.75, depth = 0.02, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)# 3D plotting
png("pred2-7.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2c, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.au.mas$durationZscore2, c(0.25))),
ylim = quantile(data.au.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.25au * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0au + global_mean0au),
transform = function(f1Zscore2) f1Zscore2 * global_sd1au + global_mean1au,
zlim = c(490,720),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.253736 to 1.355745.
* durationZscore2 : numeric predictor; set to the value(s): -0.680380067515762.
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(490,720), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2c, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2. = quantile(data.au.mas$durationZscore2, c(0.5))),
ylim = quantile(data.au.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.5au * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0au + global_mean0au),
transform = function(f1Zscore2) f1Zscore2 * global_sd1au + global_mean1au,
zlim = c(490,720),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.253736 to 1.355745.
* durationZscore2 : numeric predictor; set to the value(s): -0.0990769355270091.
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(490,720), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2c, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.au.mas$durationZscore2, c(0.75))),
ylim = quantile(data.au.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.75au * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0au + global_mean0au),
transform = function(f1Zscore2) f1Zscore2 * global_sd1au + global_mean1au,
zlim = c(490,720),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.253736 to 1.355745.
* durationZscore2 : numeric predictor; set to the value(s): 0.530017553918074.
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(490,720), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
png("pred2-diff-3.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_diff2(gamm.model2c, view=c("measurement.no","durationZscore2"),
main = "",
comp = list(f0Zscore2 = quantile(data.au.mas$f0Zscore2, c(0.8,0.2), na.rm = T)),
ylim = quantile(data.au.mas$durationZscore2, c(0.05,0.95), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no, function(durationZscore2) durationZscore2 * global_sddau + global_meandau),
print.summary = TRUE,
sim.ci = F,
show.diff = F,
#color = "heat",
alpha.diff = 0.5,
#plot.type = "perp",
#n.grid =300,
add.color.legend = FALSE, rm.ranef = TRUE,
xlab = "Time (Normalized)", ylab = "Duration (ms)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, hide.label = T)Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* durationZscore2 : numeric predictor; with 100 values ranging from -1.441948 to 1.867158.
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
#gradientLegend(valRange=c(-50,20), length=.5, pos=.75, depth = 0.02, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
#abline(h = (1.2 * global_sdd1 + global_meand1), lty=2,lwd=2, col = "white")
dev.off()null device
1
system.time(gamm.model2d.noAR <- bam(f1Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.au.fem, method="fREML", discrete = TRUE, nthreads = ncores)
)# Auto-regressive model
system.time(gamm.model2d <- bam(f1Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.au.fem, method="fREML", discrete = TRUE, nthreads = ncores, rho = r.gamm.model2d, AR.start = data.au.fem$start)
)
Family: gaussian
Link function: identity
Formula:
f1Zscore2 ~ s(measurement.no, bs = "cr", k = 10) + s(f0Zscore2,
bs = "cr", k = 10) + s(durationZscore2, bs = "cr", k = 30) +
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + ti(measurement.no, durationZscore2,
bs = "cr", k = c(5, 12)) + ti(measurement.no, f0Zscore2,
bs = "cr", k = c(5, 8)) + ti(f0Zscore2, durationZscore2,
bs = "cr", k = c(8, 12)) + s(word, bs = "re") + s(wordPos,
bs = "re") + s(wordLeftRightTone, bs = "re") + s(wordPos,
measurement.no, bs = "re") + s(wordPos, f0Zscore2, bs = "re") +
s(wordPos, durationZscore2, bs = "re") + s(wordLeftRightTone,
measurement.no, bs = "re") + s(wordLeftRightTone, f0Zscore2,
bs = "re") + s(wordLeftRightTone, durationZscore2, bs = "re") +
s(word, measurement.no, bs = "re") + s(word, f0Zscore2, bs = "re") +
s(word, durationZscore2, bs = "re") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speaker, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(measurement.no, speakerPos, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(durationZscore2, speakerPos, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(durationZscore2, speakerLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.01375 0.04473 0.307 0.759
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 8.169 8.388 122.102 <2e-16 ***
s(f0Zscore2) 1.996 2.172 0.769 0.523
s(durationZscore2) 1.000 1.000 0.358 0.550
ti(measurement.no,f0Zscore2,durationZscore2) 28.296 42.725 0.934 0.597
ti(measurement.no,durationZscore2) 11.748 14.646 5.500 <2e-16 ***
ti(measurement.no,f0Zscore2) 9.712 12.616 6.688 <2e-16 ***
ti(f0Zscore2,durationZscore2) 12.318 15.965 1.024 0.429
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.763 Deviance explained = 79.9%
fREML = 7714.8 Scale est. = 0.22484 n = 9332
Method: fREML Optimizer: perf chol
$grad
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[7] -1.798561e-14 1.585398e-13 1.549871e-13 1.794120e-13 8.393286e-14 -1.207923e-13
[13] 9.947598e-14 -5.263191e-05 -6.483702e-14 3.836931e-13 -1.243450e-13 -9.059420e-14
[19] -6.963319e-13 -2.842171e-14 9.237056e-14 5.258016e-13 -5.385358e-05 -6.177734e-05
[25] 1.598721e-13 -3.620603e-05 -1.723066e-13 -3.620603e-05 5.009326e-13 -3.620603e-05
[31] -3.268497e-13 7.194245e-14 2.273737e-13 -3.530509e-14 -1.207923e-13 -8.970602e-14
[37] 3.979039e-13 1.012523e-13 1.278977e-13 7.904788e-14 1.492140e-13 -2.753353e-13
[43] -3.183231e-11
$hess
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-1.094904e-05 -5.619199e-09 -1.249313e-05 -5.619199e-09 -5.550326e-05 -5.619199e-09
[,31] [,32] [,33] [,34] [,35] [,36]
-1.385982e-02 3.389515e-04 7.726551e-03 3.389515e-04 7.103197e-04 3.389515e-04
1.402268e-02 -6.271047e-04 -3.498037e-02 -6.271047e-04 9.269839e-03 -6.271047e-04
1.257083e-07 -6.065322e-09 -6.884602e-06 -6.065322e-09 -2.350812e-07 -6.065322e-09
1.161764e-01 -6.511501e-04 1.723055e-03 -6.511501e-04 -3.587591e-02 -6.511501e-04
5.964604e-02 8.710931e-04 -1.932493e-02 8.710931e-04 1.906095e-02 8.710931e-04
-2.108326e-02 3.500532e-03 -1.143800e-02 3.500532e-03 -2.009814e-02 3.500532e-03
2.899256e-03 -1.386158e-03 1.789674e-02 -1.386158e-03 -4.912638e-03 -1.386158e-03
3.701481e-02 -1.166805e-03 -3.960796e-02 -1.166805e-03 -2.228652e-02 -1.166805e-03
2.660998e-02 1.048228e-03 -2.140103e-02 1.048228e-03 -3.224757e-02 1.048228e-03
-2.211772e-02 -2.359295e-03 5.337264e-02 -2.359295e-03 -3.879344e-02 -2.359295e-03
5.322684e-02 -1.479645e-03 -1.028497e-02 -1.479645e-03 -2.616268e-02 -1.479645e-03
3.712809e-02 5.969998e-03 -1.858466e-01 5.969998e-03 -1.210287e-02 5.969998e-03
1.042753e-01 -3.533928e-02 8.666140e-01 -3.533928e-02 1.754822e-01 -3.533928e-02
4.654388e-06 -3.400834e-06 7.566639e-05 -3.400834e-06 -2.118735e-05 -3.400834e-06
3.910451e-02 -7.995427e-03 1.254902e-01 -7.995427e-03 -3.713318e-02 -7.995427e-03
-4.208512e-01 -1.331573e-02 -2.938254e-01 -1.331573e-02 -7.662415e-02 -1.331573e-02
1.085705e-01 3.035147e-02 7.779273e-01 3.035147e-02 1.519828e-02 3.035147e-02
2.287510e-02 -8.296763e-03 4.540896e-01 -8.296763e-03 -3.442227e-02 -8.296763e-03
2.215770e-02 -1.417913e-02 9.626192e-02 -1.417912e-02 2.688760e-01 -1.417912e-02
9.680274e-04 2.038789e-02 8.345274e-01 2.038789e-02 -9.665322e-02 2.038789e-02
3.966300e-02 2.156311e-02 7.922995e-01 2.156311e-02 1.182360e-02 2.156311e-02
-5.690763e-02 -5.216437e-03 -1.716680e-01 -5.216437e-03 4.375077e-03 -5.216437e-03
3.041693e-05 1.264864e-06 5.827101e-05 1.264864e-06 -2.239107e-05 1.264864e-06
[,37] [,38] [,39] [,40] [,41] [,42]
3.034540e-02 1.854930e-03 1.726933e-03 1.854930e-03 -6.492316e-03 1.854930e-03
5.233935e-02 -7.379720e-03 -3.604561e-02 -7.379720e-03 4.032329e-02 -7.379719e-03
2.590630e-07 -2.292569e-08 -3.721626e-06 -2.292569e-08 -5.367256e-08 -2.292569e-08
8.230710e-03 -1.337555e-03 2.459634e-02 -1.337555e-03 -1.828582e-02 -1.337555e-03
-1.859498e-02 1.386181e-03 -6.034788e-02 1.386181e-03 4.872964e-02 1.386181e-03
-7.125620e-02 -3.775344e-05 -3.660959e-03 -3.775343e-05 3.554889e-02 -3.775343e-05
1.963645e-02 5.601187e-03 1.694717e-02 5.601187e-03 2.547934e-02 5.601187e-03
5.699814e-02 -3.529290e-03 2.362316e-02 -3.529290e-03 -2.874923e-03 -3.529290e-03
1.073117e-02 1.761930e-04 -1.519782e-02 1.761930e-04 -2.392031e-02 1.761930e-04
-6.156893e-02 -2.644516e-03 -9.967163e-03 -2.644516e-03 1.653575e-02 -2.644516e-03
7.335508e-02 -7.585769e-03 -5.588337e-02 -7.585769e-03 2.233629e-02 -7.585769e-03
4.052034e-02 -1.243587e-02 -9.023810e-03 -1.243587e-02 4.874589e-03 -1.243587e-02
4.255857e-01 1.660893e-01 1.527786e+00 1.660893e-01 5.655430e-01 1.660893e-01
-4.068997e-06 1.443652e-06 2.084108e-05 1.443652e-06 -9.354291e-07 1.443652e-06
-9.837447e-02 5.669977e-02 1.165786e-01 5.669977e-02 1.029714e-01 5.669977e-02
8.932004e-01 -7.371447e-02 -8.956084e-02 -7.371447e-02 -1.842095e-01 -7.371447e-02
3.830638e-02 -4.039447e-02 3.403796e-01 -4.039447e-02 2.309060e-01 -4.039447e-02
4.945708e-02 -1.093331e-02 4.745003e-01 -1.093331e-02 1.906744e-01 -1.093331e-02
2.048780e+00 1.914477e-01 -5.244093e-02 1.914477e-01 4.951434e-01 1.914477e-01
2.072210e-01 -8.054736e-02 1.056413e+00 -8.054736e-02 1.384455e+00 -8.054736e-02
1.011093e-01 -8.843048e-02 1.408717e+00 -8.843048e-02 1.935702e-01 -8.843048e-02
8.572205e-01 1.724803e-02 4.018319e-02 1.724803e-02 2.227686e-01 1.724803e-02
1.931595e-06 -1.880187e-05 8.405210e-05 -1.880187e-05 1.480453e-04 -1.880187e-05
[,43]
-3.584358e+00
-4.979314e-01
-3.995173e-06
-4.224295e+00
-4.992701e+00
-4.430823e+00
-1.778852e+00
-3.594938e+00
-1.890926e+00
-2.465184e+00
-2.888071e+00
-2.770857e+00
-7.420494e+01
-1.405915e-03
-5.567671e+00
-6.784043e+01
-2.488542e+01
-1.469753e+01
-6.996221e+01
-5.483706e+01
-1.749645e+01
-4.127840e+01
-6.502722e-03
[ getOption("max.print") est atteint -- 20 lignes omises ]
Model rank = 10181 / 10181
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00e+00 8.17e+00 0.99 0.20
s(f0Zscore2) 9.00e+00 2.00e+00 0.99 0.18
s(durationZscore2) 2.90e+01 1.00e+00 1.07 1.00
ti(measurement.no,f0Zscore2,durationZscore2) 3.08e+02 2.83e+01 1.00 0.39
ti(measurement.no,durationZscore2) 4.40e+01 1.17e+01 1.01 0.73
ti(measurement.no,f0Zscore2) 2.80e+01 9.71e+00 1.01 0.88
ti(f0Zscore2,durationZscore2) 7.70e+01 1.23e+01 1.02 0.94
s(word) 3.10e+02 1.48e+02 NA NA
s(wordPos) 4.62e+02 2.92e-03 NA NA
s(wordLeftRightTone) 4.22e+02 1.11e+01 NA NA
s(measurement.no,wordPos) 4.62e+02 1.36e+02 NA NA
s(f0Zscore2,wordPos) 4.62e+02 4.98e+01 NA NA
s(durationZscore2,wordPos) 4.62e+02 2.94e+01 NA NA
s(measurement.no,wordLeftRightTone) 4.22e+02 1.40e+02 NA NA
s(f0Zscore2,wordLeftRightTone) 4.22e+02 1.10e+02 NA NA
s(durationZscore2,wordLeftRightTone) 4.22e+02 3.50e+01 NA NA
s(measurement.no,word) 3.10e+02 8.26e+01 NA NA
s(f0Zscore2,word) 3.10e+02 1.31e-02 NA NA
s(durationZscore2,word) 3.10e+02 1.47e-03 NA NA
s(measurement.no,speaker) 1.00e+02 5.13e+01 0.99 0.20
s(durationZscore2,speaker) 3.00e+02 2.03e+01 1.07 1.00
s(f0Zscore2,speaker) 1.00e+02 4.41e+01 0.99 0.18
s(measurement.no,speakerPos) 3.00e+02 5.14e+01 0.99 0.21
s(durationZscore2,speakerPos) 9.00e+02 8.25e+01 1.07 1.00
s(f0Zscore2,speakerPos) 3.00e+02 3.78e+01 0.99 0.20
s(measurement.no,speakerLeftRightTone) 5.80e+02 1.07e+02 0.99 0.21
s(durationZscore2,speakerLeftRightTone) 1.74e+03 9.60e+01 1.07 1.00
s(f0Zscore2,speakerLeftRightTone) 5.80e+02 8.20e+01 0.99 0.17
duration0.25auf = quantile(data.au.fem$durationZscore2, c(0.25)) * global_sddauf + global_meandauf
duration0.5auf = quantile(data.au.fem$durationZscore2, c(0.5)) * global_sddauf + global_meandauf
duration0.75auf = quantile(data.au.fem$durationZscore2, c(0.75)) * global_sddauf + global_meandauf# 3D plotting
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2d, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.au.fem$durationZscore2, c(0.25))),
ylim = quantile(data.au.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.25auf * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0auf + global_mean0auf),
transform = function(f1Zscore2) f1Zscore2 * global_sd1auf + global_mean1auf,
zlim = c(500,900),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.270026 to 1.307646.
* durationZscore2 : numeric predictor; set to the value(s): -0.65512883823603.
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(500,900), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))fvisgam(gamm.model2d, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2. = quantile(data.au.fem$durationZscore2, c(0.5))),
ylim = quantile(data.au.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.5auf * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0auf + global_mean0auf),
transform = function(f1Zscore2) f1Zscore2 * global_sd1auf + global_mean1auf,
zlim = c(500,900),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.270026 to 1.307646.
* durationZscore2 : numeric predictor; set to the value(s): -0.135002585755248.
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(500,900), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))fvisgam(gamm.model2d, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.au.fem$durationZscore2, c(0.75))),
ylim = quantile(data.au.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.75auf * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0auf + global_mean0auf),
transform = function(f1Zscore2) f1Zscore2 * global_sd1auf + global_mean1auf,
zlim = c(500,900),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.270026 to 1.307646.
* durationZscore2 : numeric predictor; set to the value(s): 0.536034051323852.
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(500,900), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_diff2(gamm.model2d, view=c("measurement.no","durationZscore2"),
main = "",
comp = list(f0Zscore2 = quantile(data.au.fem$f0Zscore2, c(0.8,0.2), na.rm = T)),
ylim = quantile(data.au.fem$durationZscore2, c(0.05,0.95), na.rm = T),
transform.view = c(function(measurement.no) measurement.no, function(durationZscore2) durationZscore2 * global_sddauf + global_meandauf),
#zlim = c(-0.5,0.5),
print.summary = TRUE,
sim.ci = F,
show.diff = F,
#color = "heat",
alpha.diff = 0.5,
#plot.type = "perp",
#n.grid =300,
add.color.legend = FALSE, rm.ranef = TRUE,
xlab = "Time (Normalized)", ylab = "Duration (ms)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, hide.label = T)Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* durationZscore2 : numeric predictor; with 30 values ranging from -1.395442 to 1.808743.
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
#gradientLegend(valRange=c(-50,20), length=.5, pos=.75, depth = 0.02, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)# 3D plotting
png("pred2-10.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2d, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.au.fem$durationZscore2, c(0.25))),
ylim = quantile(data.au.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.25auf * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0auf + global_mean0auf),
transform = function(f1Zscore2) f1Zscore2 * global_sd1auf + global_mean1auf,
zlim = c(500,900),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.270026 to 1.307646.
* durationZscore2 : numeric predictor; set to the value(s): -0.65512883823603.
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(500,900), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2d, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2. = quantile(data.au.fem$durationZscore2, c(0.5))),
ylim = quantile(data.au.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.5auf * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0auf + global_mean0auf),
transform = function(f1Zscore2) f1Zscore2 * global_sd1auf + global_mean1auf,
zlim = c(500,900),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.270026 to 1.307646.
* durationZscore2 : numeric predictor; set to the value(s): -0.135002585755248.
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(500,900), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2d, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.au.fem$durationZscore2, c(0.75))),
ylim = quantile(data.au.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.75auf * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0auf + global_mean0auf),
transform = function(f1Zscore2) f1Zscore2 * global_sd1auf + global_mean1auf,
zlim = c(500,900),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.270026 to 1.307646.
* durationZscore2 : numeric predictor; set to the value(s): 0.536034051323852.
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(500,900), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
png("pred2-diff-4.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
plot_diff2(gamm.model2d, view=c("measurement.no","durationZscore2"),
main = "",
comp = list(f0Zscore2 = quantile(data.au.fem$f0Zscore2, c(0.8,0.2), na.rm = T)),
ylim = quantile(data.au.fem$durationZscore2, c(0.05,0.95), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no, function(durationZscore2) durationZscore2 * global_sddauf + global_meandauf),
print.summary = TRUE,
sim.ci = F,
show.diff = F,
#color = "heat",
alpha.diff = 0.5,
#plot.type = "perp",
#n.grid =300,
add.color.legend = FALSE, rm.ranef = TRUE,
xlab = "Time (Normalized)", ylab = "Duration (ms)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, hide.label = T)Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* durationZscore2 : numeric predictor; with 100 values ranging from -1.395442 to 1.808743.
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
#gradientLegend(valRange=c(-50,20), length=.5, pos=.75, depth = 0.02, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols)
axis(1, at=tickvals, labels=ticknames, las=1, cex.axis=1)
#abline(h = (1.2 * global_sdd1 + global_meand1), lty=2,lwd=2, col = "white")
dev.off()null device
1
system.time(gamm.model2e.noAR <- bam(f2Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.ai.mas, method="fREML", discrete = TRUE, nthreads = ncores)
)system.time(gamm.model2e <- bam(f2Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.ai.mas, method="fREML", discrete = TRUE, nthreads = ncores, rho = r.gamm.model2e, AR.start = data.ai.mas$start)
)
Family: gaussian
Link function: identity
Formula:
f2Zscore2 ~ s(measurement.no, bs = "cr", k = 10) + s(f0Zscore2,
bs = "cr", k = 10) + s(durationZscore2, bs = "cr", k = 30) +
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + ti(measurement.no, durationZscore2,
bs = "cr", k = c(5, 12)) + ti(measurement.no, f0Zscore2,
bs = "cr", k = c(5, 8)) + ti(f0Zscore2, durationZscore2,
bs = "cr", k = c(8, 12)) + s(word, bs = "re") + s(wordPos,
bs = "re") + s(wordLeftRightTone, bs = "re") + s(wordPos,
measurement.no, bs = "re") + s(wordPos, f0Zscore2, bs = "re") +
s(wordPos, durationZscore2, bs = "re") + s(wordLeftRightTone,
measurement.no, bs = "re") + s(wordLeftRightTone, f0Zscore2,
bs = "re") + s(wordLeftRightTone, durationZscore2, bs = "re") +
s(word, measurement.no, bs = "re") + s(word, f0Zscore2, bs = "re") +
s(word, durationZscore2, bs = "re") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speaker, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(measurement.no, speakerPos, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(durationZscore2, speakerPos, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(durationZscore2, speakerLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.03309 0.06372 -0.519 0.603
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 6.587 7.036 42.221 < 2e-16 ***
s(f0Zscore2) 1.001 1.001 0.704 0.40177
s(durationZscore2) 1.000 1.000 0.070 0.79155
ti(measurement.no,f0Zscore2,durationZscore2) 43.112 63.333 1.502 0.00624 **
ti(measurement.no,durationZscore2) 8.124 10.520 8.408 < 2e-16 ***
ti(measurement.no,f0Zscore2) 9.596 12.833 1.324 0.18437
ti(f0Zscore2,durationZscore2) 4.004 5.519 0.724 0.58084
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.762 Deviance explained = 79.6%
fREML = 7659.4 Scale est. = 0.1865 n = 11029
Method: fREML Optimizer: perf chol
$grad
[1] -6.466605e-11 -1.099589e-04 -8.205627e-05 -9.580248e-11 -5.427037e-11 2.728839e-11 -3.064549e-11 -5.168244e-11 7.965251e-11
[10] -1.480534e-09 -2.779021e-11 -2.173628e-11 2.299601e-10 -1.102833e-10 2.218954e-10 -3.369180e-10 -1.183778e-09 1.015632e-12
[19] -7.514487e-10 -1.523663e-09 7.680612e-11 -8.705854e-10 -7.873306e-10 -6.887912e-11 3.979395e-11 -4.629656e-05 2.742766e-10
[28] -4.629656e-05 -6.677240e-05 -4.629656e-05 -1.087983e-10 -8.439471e-12 2.441283e-10 -8.387957e-12 -6.500755e-11 -8.248069e-12
[37] -1.099849e-10 -5.539125e-12 2.314096e-10 -5.528911e-12 -1.287361e-10 -5.548895e-12 1.035460e-08
$hess
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
2.499957e+00 -1.856674e-06 -1.653204e-08 -1.508445e-02 -1.672591e-03 4.329405e-03 4.331140e-03 4.650016e-03 -6.754962e-02
-1.856674e-06 1.099444e-04 1.020838e-11 1.393029e-05 3.427163e-06 3.938975e-06 -4.040920e-06 1.819914e-06 3.413605e-06
-1.653204e-08 1.020838e-11 8.204896e-05 -1.815967e-07 -2.755302e-07 -2.001405e-07 8.574229e-08 -8.465774e-07 -3.572615e-08
-1.508445e-02 1.393029e-05 -1.815967e-07 2.017139e+00 2.915528e-01 2.097776e-01 1.252796e-04 -6.317605e-02 -4.054230e-02
-1.672591e-03 3.427163e-06 -2.755302e-07 2.915528e-01 1.362692e+00 -2.210867e-02 6.593857e-03 4.478569e-03 -3.364210e-02
4.329405e-03 3.938975e-06 -2.001405e-07 2.097776e-01 -2.210867e-02 1.227583e+00 -5.263585e-03 -5.290433e-02 1.008190e-02
4.331140e-03 -4.040920e-06 8.574229e-08 1.252796e-04 6.593857e-03 -5.263585e-03 8.333206e-01 2.867781e-01 -3.340592e-02
4.650016e-03 1.819914e-06 -8.465774e-07 -6.317605e-02 4.478569e-03 -5.290433e-02 2.867781e-01 7.909208e-01 -1.490027e-02
-6.754962e-02 3.413605e-06 -3.572615e-08 -4.054230e-02 -3.364210e-02 1.008190e-02 -3.340592e-02 -1.490027e-02 6.294332e-01
-2.746060e-02 -6.276876e-05 6.140013e-08 4.948368e-03 -3.964251e-02 -8.079063e-03 9.786722e-05 1.553199e-02 4.819707e-02
3.353791e-03 -2.192985e-06 2.788012e-08 -7.919451e-03 -1.590065e-02 4.658552e-03 -1.651135e-02 3.210911e-02 6.092042e-04
1.429716e-04 -6.574118e-07 1.851162e-07 4.083438e-03 -1.125033e-04 -1.252218e-02 -1.212269e-02 9.956261e-02 3.256245e-03
1.694969e-02 3.095005e-05 -4.186345e-07 -8.227189e-03 -2.994921e-02 -2.731581e-02 -2.615180e-04 5.693877e-02 -1.983557e-02
5.032234e-03 1.543397e-05 -4.960672e-07 -8.758516e-03 1.935703e-02 3.199550e-02 5.345708e-03 3.775872e-02 -7.938288e-03
-5.214725e-03 1.899218e-05 -8.057912e-07 -3.949872e-02 -4.525950e-02 -2.620752e-02 1.215210e-02 2.274698e-02 -3.310704e-02
-6.913185e-03 1.691916e-05 1.296798e-07 -1.682020e-02 -1.317589e-01 -1.532159e-01 -3.759230e-02 -7.200230e-02 -5.290230e-03
1.378823e-03 2.730559e-07 1.393753e-07 6.044157e-03 2.064937e-02 2.916193e-02 8.434014e-03 6.628455e-02 5.072443e-04
5.526265e-04 -6.456164e-08 -2.763226e-07 1.337846e-03 1.023882e-03 2.879178e-03 -1.877102e-03 -3.381944e-03 1.018394e-03
-2.965836e-03 -6.754807e-06 -6.707781e-07 4.890695e-02 4.617717e-02 -8.166221e-02 -1.426889e-02 2.553092e-02 2.861862e-03
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[ getOption("max.print") est atteint -- 20 lignes omises ]
Model rank = 8855 / 8855
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00e+00 6.59e+00 0.99 0.305
s(f0Zscore2) 9.00e+00 1.00e+00 1.00 0.545
s(durationZscore2) 2.90e+01 1.00e+00 0.99 0.145
ti(measurement.no,f0Zscore2,durationZscore2) 3.08e+02 4.31e+01 0.95 <2e-16 ***
ti(measurement.no,durationZscore2) 4.40e+01 8.12e+00 1.03 0.970
ti(measurement.no,f0Zscore2) 2.80e+01 9.60e+00 1.01 0.675
ti(f0Zscore2,durationZscore2) 7.70e+01 4.00e+00 0.98 0.065 .
s(word) 2.09e+02 6.40e+01 NA NA
s(wordPos) 3.31e+02 4.65e+01 NA NA
s(wordLeftRightTone) 3.10e+02 7.07e+01 NA NA
s(measurement.no,wordPos) 3.31e+02 8.85e+01 NA NA
s(f0Zscore2,wordPos) 3.31e+02 5.17e+01 NA NA
s(durationZscore2,wordPos) 3.31e+02 4.09e+00 NA NA
s(measurement.no,wordLeftRightTone) 3.10e+02 9.93e+01 NA NA
s(f0Zscore2,wordLeftRightTone) 3.10e+02 4.75e+01 NA NA
s(durationZscore2,wordLeftRightTone) 3.10e+02 4.41e+01 NA NA
s(measurement.no,word) 2.09e+02 9.96e+01 NA NA
s(f0Zscore2,word) 2.09e+02 4.93e+00 NA NA
s(durationZscore2,word) 2.09e+02 1.42e+01 NA NA
s(measurement.no,speaker) 1.00e+02 3.84e+01 0.99 0.285
s(durationZscore2,speaker) 3.00e+02 1.04e+02 0.99 0.155
s(f0Zscore2,speaker) 1.00e+02 4.19e-03 1.00 0.505
s(measurement.no,speakerPos) 3.00e+02 7.37e+01 0.99 0.320
s(durationZscore2,speakerPos) 9.00e+02 1.05e+02 0.99 0.195
s(f0Zscore2,speakerPos) 3.00e+02 6.74e+01 1.00 0.515
s(measurement.no,speakerLeftRightTone) 5.90e+02 1.17e+02 0.99 0.245
s(durationZscore2,speakerLeftRightTone) 1.77e+03 2.59e+02 0.99 0.100 .
s(f0Zscore2,speakerLeftRightTone) 5.90e+02 1.11e+02 1.00 0.580
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
# Plotting
# 3D plot
# png("pred2b-1.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2e, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.25))),
ylim = quantile(data.ai.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.25 * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0 + global_mean0),
transform = function(f2Zscore2) f2Zscore2 * global_sd2 + global_mean2,
zlim = c(1400,1900),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.266227 to 1.296824.
* durationZscore2 : numeric predictor; set to the value(s): -0.449662795901817.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(1400,1900), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
# dev.off()
# png("pred2b-2.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))fvisgam(gamm.model2e, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.5))),
ylim = quantile(data.ai.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.5 * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0 + global_mean0),
transform = function(f2Zscore2) f2Zscore2 * global_sd2 + global_mean2,
zlim = c(1400,1900),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.266227 to 1.296824.
* durationZscore2 : numeric predictor; set to the value(s): 0.0671853722597352.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(1400,1900), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
# dev.off()
# png("pred2b-3.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))fvisgam(gamm.model2e, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.75))),
ylim = quantile(data.ai.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.75 * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0 + global_mean0),
transform = function(f2Zscore2) f2Zscore2 * global_sd2 + global_mean2,
zlim = c(1400,1900),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.266227 to 1.296824.
* durationZscore2 : numeric predictor; set to the value(s): 0.637773887350503.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(1400,1900), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)# Plotting
# 3D plot
png("pred2b-1.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2e, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.25))),
ylim = quantile(data.ai.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.25 * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0 + global_mean0),
transform = function(f2Zscore2) f2Zscore2 * global_sd2 + global_mean2,
zlim = c(1400,1900),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.266227 to 1.296824.
* durationZscore2 : numeric predictor; set to the value(s): -0.449662795901817.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(1400,1900), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2e, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.5))),
ylim = quantile(data.ai.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.5 * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0 + global_mean0),
transform = function(f2Zscore2) f2Zscore2 * global_sd2 + global_mean2,
zlim = c(1400,1900),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.266227 to 1.296824.
* durationZscore2 : numeric predictor; set to the value(s): 0.0671853722597352.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(1400,1900), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2e, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.mas$durationZscore2, c(0.75))),
ylim = quantile(data.ai.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.75 * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0 + global_mean0),
transform = function(f2Zscore2) f2Zscore2 * global_sd2 + global_mean2,
zlim = c(1400,1900),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.266227 to 1.296824.
* durationZscore2 : numeric predictor; set to the value(s): 0.637773887350503.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Deb. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 H H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0011. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0006 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0002 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(1400,1900), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
system.time(gamm.model2f.noAR <- bam(f2Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.ai.fem, method="fREML", discrete = TRUE, nthreads = ncores)
)system.time(gamm.model2f <- bam(f2Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.ai.fem, method="fREML", discrete = TRUE, nthreads = ncores, rho = r.gamm.model2f, AR.start = data.ai.fem$start)
)
Family: gaussian
Link function: identity
Formula:
f2Zscore2 ~ s(measurement.no, bs = "cr", k = 10) + s(f0Zscore2,
bs = "cr", k = 10) + s(durationZscore2, bs = "cr", k = 30) +
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + ti(measurement.no, durationZscore2,
bs = "cr", k = c(5, 12)) + ti(measurement.no, f0Zscore2,
bs = "cr", k = c(5, 8)) + ti(f0Zscore2, durationZscore2,
bs = "cr", k = c(8, 12)) + s(word, bs = "re") + s(wordPos,
bs = "re") + s(wordLeftRightTone, bs = "re") + s(wordPos,
measurement.no, bs = "re") + s(wordPos, f0Zscore2, bs = "re") +
s(wordPos, durationZscore2, bs = "re") + s(wordLeftRightTone,
measurement.no, bs = "re") + s(wordLeftRightTone, f0Zscore2,
bs = "re") + s(wordLeftRightTone, durationZscore2, bs = "re") +
s(word, measurement.no, bs = "re") + s(word, f0Zscore2, bs = "re") +
s(word, durationZscore2, bs = "re") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speaker, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(measurement.no, speakerPos, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(durationZscore2, speakerPos, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(durationZscore2, speakerLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.001353 0.068175 0.02 0.984
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 1.000 1.000 43.012 < 2e-16 ***
s(f0Zscore2) 1.299 1.383 1.414 0.3345
s(durationZscore2) 1.000 1.000 1.746 0.1864
ti(measurement.no,f0Zscore2,durationZscore2) 7.153 11.575 0.330 0.9841
ti(measurement.no,durationZscore2) 11.826 15.816 3.599 1.74e-06 ***
ti(measurement.no,f0Zscore2) 6.133 8.041 2.059 0.0377 *
ti(f0Zscore2,durationZscore2) 1.990 2.644 0.067 0.9769
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.565 Deviance explained = 61.7%
fREML = 10576 Scale est. = 0.39103 n = 10275
Method: fREML Optimizer: perf chol
$grad
[1] -4.059069e-05 -3.621745e-11 -6.621412e-05 -2.511880e-12 9.776513e-12 1.672240e-11 2.539258e-11 -2.151834e-11 8.259393e-12
[10] 2.543565e-11 -4.782791e-11 -4.194253e-11 -1.131390e-09 -1.109672e-10 -6.864180e-10 3.423395e-11 -2.213056e-10 -8.591172e-10
[19] 1.992291e-10 -7.025869e-05 -8.696881e-05 5.742606e-11 -3.369820e-10 -3.685521e-10 -2.665956e-11 -1.379341e-12 -3.918283e-05
[28] -1.368031e-12 8.075673e-11 -1.376385e-12 5.211120e-11 1.643352e-12 4.817480e-12 1.604161e-12 6.907186e-11 1.598943e-12
[37] 3.115730e-11 3.152856e-11 2.128644e-10 3.161116e-11 -6.675549e-11 3.155920e-11 1.219723e-08
$hess
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1.628755e-02 1.250722e-03 2.714633e-02 1.250722e-03 8.180883e-03 1.250722e-03 -1.293794e+00
-6.609396e-02 5.814416e-03 4.953492e-02 5.814416e-03 8.360095e-02 5.814416e-03 -2.180152e+00
2.728893e-02 1.277839e-03 1.063570e-01 1.277839e-03 -8.030345e-02 1.277839e-03 -3.232756e+00
-3.725881e-02 2.750189e-03 2.566467e-03 2.750189e-03 -1.775884e-02 2.750189e-03 -1.196251e+00
-1.604958e-02 4.341278e-03 4.589217e-02 4.341278e-03 -1.729495e-02 4.341278e-03 -1.370127e+00
-5.598287e-05 -5.696725e-04 7.848316e-04 -5.696725e-04 1.743347e-02 -5.696725e-04 -2.512830e-01
-1.768843e-03 1.058570e-04 1.421523e-02 1.058570e-04 1.830551e-02 1.058570e-04 -2.437146e-01
1.383733e-01 -1.543944e-02 4.372202e-01 -1.543944e-02 -1.357168e-01 -1.543944e-02 -3.504332e+01
4.719865e-02 1.457266e-02 1.727387e-01 1.457266e-02 -7.422392e-02 1.457266e-02 -1.313519e+01
-4.092469e-02 8.190201e-04 -1.554662e-01 8.190201e-04 -5.434497e-03 8.190201e-04 -3.235735e+00
-1.251299e-01 9.712825e-02 2.496001e-02 9.712825e-02 2.167738e-01 9.712825e-02 -4.640936e+01
-2.267620e-01 -4.018950e-02 -8.049615e-01 -4.018950e-02 2.460837e-01 -4.018950e-02 -3.537426e+01
1.346285e-01 -1.511220e-02 3.178864e-01 -1.511220e-02 -1.666556e-01 -1.511220e-02 -1.571325e+01
-1.912494e-01 -1.766386e-01 -7.311826e-01 -1.766386e-01 2.367257e-01 -1.766386e-01 -4.916784e+01
-1.584603e-06 4.743486e-07 -1.235287e-05 4.743486e-07 1.746024e-05 4.743486e-07 -5.001692e-04
5.573328e-05 -5.663561e-06 6.961738e-05 -5.663561e-06 7.516810e-06 -5.663561e-06 -3.279942e-03
-1.733565e-01 -3.382266e-02 -4.885975e-01 -3.382266e-02 1.222144e-01 -3.382266e-02 -3.980497e+01
1.482106e-01 1.408333e-02 8.745991e-02 1.408333e-02 2.004322e-01 1.408333e-02 -1.760626e+01
[ getOption("max.print") est atteint -- 20 lignes omises ]
Model rank = 8663 / 8663
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00e+00 1.00e+00 1.00 0.390
s(f0Zscore2) 9.00e+00 1.30e+00 0.99 0.285
s(durationZscore2) 2.90e+01 1.00e+00 0.99 0.255
ti(measurement.no,f0Zscore2,durationZscore2) 3.08e+02 7.15e+00 1.01 0.660
ti(measurement.no,durationZscore2) 4.40e+01 1.18e+01 1.01 0.845
ti(measurement.no,f0Zscore2) 2.80e+01 6.13e+00 1.01 0.880
ti(f0Zscore2,durationZscore2) 7.70e+01 1.99e+00 0.98 0.075 .
s(word) 2.03e+02 7.01e+01 NA NA
s(wordPos) 3.09e+02 2.63e+01 NA NA
s(wordLeftRightTone) 2.90e+02 6.47e+00 NA NA
s(measurement.no,wordPos) 3.09e+02 9.28e+01 NA NA
s(f0Zscore2,wordPos) 3.09e+02 7.07e+01 NA NA
s(durationZscore2,wordPos) 3.09e+02 3.14e+01 NA NA
s(measurement.no,wordLeftRightTone) 2.90e+02 9.83e+01 NA NA
s(f0Zscore2,wordLeftRightTone) 2.90e+02 1.14e-03 NA NA
s(durationZscore2,wordLeftRightTone) 2.90e+02 6.73e-03 NA NA
s(measurement.no,word) 2.03e+02 7.96e+01 NA NA
s(f0Zscore2,word) 2.03e+02 3.52e+01 NA NA
s(durationZscore2,word) 2.03e+02 2.21e+00 NA NA
s(measurement.no,speaker) 1.00e+02 5.00e+01 1.00 0.370
s(durationZscore2,speaker) 3.00e+02 1.52e-01 0.99 0.245
s(f0Zscore2,speaker) 1.00e+02 3.44e+01 0.99 0.300
s(measurement.no,speakerPos) 3.00e+02 4.09e+01 1.00 0.420
s(durationZscore2,speakerPos) 9.00e+02 1.34e+02 0.99 0.230
s(f0Zscore2,speakerPos) 3.00e+02 4.96e+01 0.99 0.260
s(measurement.no,speakerLeftRightTone) 5.90e+02 7.93e+01 1.00 0.360
s(durationZscore2,speakerLeftRightTone) 1.77e+03 2.35e+02 0.99 0.210
s(f0Zscore2,speakerLeftRightTone) 5.90e+02 7.52e+01 0.99 0.235
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
# Plotting
# 3D plot
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2f, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.fem$durationZscore2, c(0.25))),
ylim = quantile(data.ai.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.25f * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0f + global_mean0f),
transform = function(f2Zscore2) f2Zscore2 * global_sd2f + global_mean2f,
zlim = c(1700,2100),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.243937 to 1.329686.
* durationZscore2 : numeric predictor; set to the value(s): -0.627777955022104.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(1700,2100), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))fvisgam(gamm.model2f, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.fem$durationZscore2, c(0.5))),
ylim = quantile(data.ai.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.5f * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0f + global_mean0f),
transform = function(f2Zscore2) f2Zscore2 * global_sd2f + global_mean2f,
zlim = c(1700,2100),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.243937 to 1.329686.
* durationZscore2 : numeric predictor; set to the value(s): -0.0941417149129249.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(1700,2100), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))fvisgam(gamm.model2f, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.fem$durationZscore2, c(0.75))),
ylim = quantile(data.ai.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.75f * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0f + global_mean0f),
transform = function(f2Zscore2) f2Zscore2 * global_sd2f + global_mean2f,
zlim = c(1700,2100),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.243937 to 1.329686.
* durationZscore2 : numeric predictor; set to the value(s): 0.525044865601105.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(1700,2100), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)# Plotting
# 3D plot
png("pred2b-4.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2f, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.fem$durationZscore2, c(0.25))),
ylim = quantile(data.ai.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.25f * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0f + global_mean0f),
transform = function(f2Zscore2) f2Zscore2 * global_sd2f + global_mean2f,
zlim = c(1700,2100),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.243937 to 1.329686.
* durationZscore2 : numeric predictor; set to the value(s): -0.627777955022104.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(1700,2100), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2f, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.fem$durationZscore2, c(0.5))),
ylim = quantile(data.ai.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.5f * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0f + global_mean0f),
transform = function(f2Zscore2) f2Zscore2 * global_sd2f + global_mean2f,
zlim = c(1700,2100),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.243937 to 1.329686.
* durationZscore2 : numeric predictor; set to the value(s): -0.0941417149129249.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(1700,2100), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2f, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.ai.fem$durationZscore2, c(0.75))),
ylim = quantile(data.ai.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.75f * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0f + global_mean0f),
transform = function(f2Zscore2) f2Zscore2 * global_sd2f + global_mean2f,
zlim = c(1700,2100),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.243937 to 1.329686.
* durationZscore2 : numeric predictor; set to the value(s): 0.525044865601105.
* word : factor; set to the value(s): 在. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 在 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 在 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0130. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0130 Med. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0130 H H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(1700,2100), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
system.time(gamm.model2g.noAR <- bam(f2Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.au.mas, method="fREML", discrete = TRUE, nthreads = ncores)
)# Auto-regressive model
system.time(gamm.model2g <- bam(f2Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.au.mas, method="fREML", discrete = TRUE, nthreads = ncores, rho = r.gamm.model2g, AR.start = data.au.mas$start)
)
Family: gaussian
Link function: identity
Formula:
f2Zscore2 ~ s(measurement.no, bs = "cr", k = 10) + s(f0Zscore2,
bs = "cr", k = 10) + s(durationZscore2, bs = "cr", k = 30) +
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + ti(measurement.no, durationZscore2,
bs = "cr", k = c(5, 12)) + ti(measurement.no, f0Zscore2,
bs = "cr", k = c(5, 8)) + ti(f0Zscore2, durationZscore2,
bs = "cr", k = c(8, 12)) + s(word, bs = "re") + s(wordPos,
bs = "re") + s(wordLeftRightTone, bs = "re") + s(wordPos,
measurement.no, bs = "re") + s(wordPos, f0Zscore2, bs = "re") +
s(wordPos, durationZscore2, bs = "re") + s(wordLeftRightTone,
measurement.no, bs = "re") + s(wordLeftRightTone, f0Zscore2,
bs = "re") + s(wordLeftRightTone, durationZscore2, bs = "re") +
s(word, measurement.no, bs = "re") + s(word, f0Zscore2, bs = "re") +
s(word, durationZscore2, bs = "re") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speaker, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(measurement.no, speakerPos, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(durationZscore2, speakerPos, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(durationZscore2, speakerLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.007337 0.065831 -0.111 0.911
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 6.857 7.407 50.956 < 2e-16 ***
s(f0Zscore2) 1.001 1.001 3.625 0.05699 .
s(durationZscore2) 1.000 1.000 6.844 0.00891 **
ti(measurement.no,f0Zscore2,durationZscore2) 64.111 88.432 1.371 0.01136 *
ti(measurement.no,durationZscore2) 12.116 14.981 7.821 < 2e-16 ***
ti(measurement.no,f0Zscore2) 12.808 16.209 3.462 3.87e-06 ***
ti(f0Zscore2,durationZscore2) 14.751 18.368 1.484 0.07181 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.768 Deviance explained = 80.9%
fREML = 7928.2 Scale est. = 0.20584 n = 9522
Method: fREML Optimizer: perf chol
$grad
[1] -1.141309e-13 -3.841662e-05 -6.293743e-05 4.643397e-12 7.320367e-12 -2.765788e-12 -9.481305e-13 -4.125589e-13 1.794120e-13
[10] 3.249845e-12 -3.369616e-11 -2.640821e-11 -1.170974e-11 3.801404e-13 8.483880e-12 9.634959e-12 -4.114042e-12 -2.496847e-11
[19] -3.993250e-12 -5.382361e-12 -1.030642e-11 1.278977e-13 6.455281e-12 -4.361409e-05 -2.280842e-12 -3.716393e-05 -1.524150e-10
[28] -3.716393e-05 -2.188028e-12 -3.716393e-05 -8.494538e-12 -6.433230e-05 -4.732925e-11 -6.433230e-05 -2.837908e-11 -6.433230e-05
[37] -8.242296e-12 -1.193712e-12 -4.510525e-11 -1.203038e-12 -2.599876e-11 -1.390443e-12 8.312782e-10
$hess
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[,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36]
3.005054e-08 2.589768e-04 3.005054e-08 -2.399594e-02 -5.370128e-08 7.591378e-03 -5.370128e-08 4.014155e-03 -5.370128e-08
5.927509e-10 7.005194e-06 5.927509e-10 -1.095698e-05 8.994257e-10 4.988482e-06 8.994257e-10 7.447891e-05 8.994257e-10
-1.346886e-10 -1.650155e-07 -1.346886e-10 -7.788173e-08 -2.141209e-10 -1.517430e-05 -2.141209e-10 -3.819572e-06 -2.141209e-10
-4.831440e-07 -5.638543e-03 -4.831440e-07 1.071179e-01 -6.547804e-07 -6.072059e-02 -6.547804e-07 -3.845532e-02 -6.547804e-07
-1.024895e-07 -1.410026e-03 -1.024895e-07 6.099236e-02 -1.747208e-06 1.015925e-02 -1.747208e-06 -1.665329e-02 -1.747208e-06
4.165546e-06 6.014370e-03 4.165546e-06 2.658481e-01 3.569838e-06 -5.593690e-02 3.569838e-06 8.406758e-02 3.569838e-06
-2.225425e-07 8.338413e-04 -2.225425e-07 8.683306e-03 -1.923825e-07 -3.296350e-03 -1.923825e-07 4.250631e-02 -1.923825e-07
-2.445570e-07 3.670315e-03 -2.445570e-07 4.390346e-03 9.283889e-07 5.471059e-02 9.283889e-07 9.096991e-03 9.283889e-07
-2.491455e-07 -3.029114e-03 -2.491455e-07 -2.518079e-02 5.240570e-07 7.251065e-03 5.240570e-07 -4.513590e-02 5.240570e-07
-7.781771e-07 -4.495596e-03 -7.781771e-07 -1.360236e-02 -2.977474e-06 -4.228874e-02 -2.977474e-06 -6.824874e-02 -2.977474e-06
5.451343e-07 -1.617003e-03 5.451343e-07 -1.326625e-02 4.268984e-06 7.554551e-02 4.268984e-06 7.760056e-02 4.268984e-06
-2.551712e-06 2.522864e-03 -2.551712e-06 9.512365e-02 2.983049e-06 6.295328e-02 2.983049e-06 1.759578e-01 2.983049e-06
7.605095e-06 -9.827437e-03 7.605095e-06 2.444763e-01 -4.213360e-06 5.171391e-01 -4.213360e-06 -4.513175e-01 -4.213360e-06
-8.846752e-07 6.059504e-03 -8.846752e-07 2.956199e-02 -2.772122e-05 3.575002e-01 -2.772122e-05 -2.914186e-01 -2.772122e-05
-3.819007e-06 4.327357e-03 -3.819007e-06 -4.756851e-02 2.383848e-05 -7.572409e-03 2.383848e-05 2.384651e-01 2.383848e-05
-1.496415e-05 -1.252884e-02 -1.496415e-05 -2.000054e-01 -5.655520e-05 4.145791e-01 -5.655520e-05 -4.082250e-01 -5.655520e-05
-2.733200e-06 -1.185679e-02 -2.733200e-06 -6.690333e-02 -8.812674e-06 -5.870370e-02 -8.812674e-06 -1.209799e+00 -8.812674e-06
5.743898e-06 3.133858e-03 5.743898e-06 8.844048e-02 9.103638e-06 6.246060e-01 9.103638e-06 1.282953e-01 9.103638e-06
1.286188e-05 1.278736e-02 1.286188e-05 -2.921554e-01 -1.071737e-05 -2.702772e-01 -1.071737e-05 2.915477e-01 -1.071737e-05
-5.250567e-06 -3.341871e-03 -5.250567e-06 -2.844092e-02 3.894293e-06 -2.869911e-01 3.894293e-06 -2.329327e-01 3.894293e-06
-2.255914e-06 -8.063697e-04 -2.255914e-06 3.505500e-02 -1.140261e-05 1.300857e-01 -1.140261e-05 2.433661e-02 -1.140261e-05
-2.040872e-06 -1.295330e-02 -2.040872e-06 -2.091751e-01 -1.673767e-05 6.633227e-02 -1.673767e-05 6.797890e-02 -1.673767e-05
-3.174914e-06 -7.608014e-03 -3.174914e-06 -3.901309e-02 1.862357e-05 -2.931420e-01 1.862357e-05 -1.486983e-01 1.862357e-05
[,37] [,38] [,39] [,40] [,41] [,42] [,43]
5.148202e-03 2.227418e-03 -3.520200e-03 2.227418e-03 -2.896279e-03 2.227418e-03 -2.928429e+00
-2.007979e-05 2.584984e-06 3.337298e-05 2.584984e-06 -2.199942e-05 2.584984e-06 -2.481696e-04
-1.547831e-06 -1.391614e-06 -6.480514e-06 -1.391614e-06 -3.158484e-07 -1.391614e-06 -2.791521e-05
3.330571e-01 9.366132e-04 9.359706e-03 9.366132e-04 2.154394e-02 9.366132e-04 -1.260142e+01
8.137558e-02 8.994266e-03 2.307253e-01 8.994266e-03 -1.004802e-01 8.994266e-03 -9.395528e+00
-1.587983e-01 3.839453e-03 1.617428e-02 3.839453e-03 3.931150e-01 3.839453e-03 -9.558610e+00
-5.640048e-03 9.295586e-04 -8.900323e-03 9.295586e-04 -4.664057e-03 9.295586e-04 -2.106781e+00
-6.229886e-02 -4.133885e-03 3.383276e-02 -4.133885e-03 6.653201e-02 -4.133885e-03 -3.451444e+00
-8.170712e-02 4.813851e-04 2.330849e-02 4.813851e-04 1.740057e-02 4.813851e-04 -2.488524e+00
7.111882e-02 -9.192905e-03 -5.669800e-02 -9.192905e-03 2.471772e-02 -9.192905e-03 -3.415491e+00
9.235468e-02 1.158516e-04 7.365949e-02 1.158516e-04 6.458454e-02 1.158516e-04 -3.126158e+00
2.162964e-02 -4.297287e-03 -1.322587e-01 -4.297287e-03 1.315309e-01 -4.297287e-03 -3.749263e+00
1.026749e+00 1.253306e-01 1.227346e+00 1.253306e-01 2.967928e-01 1.253306e-01 -9.927052e+01
1.344217e-01 -4.758047e-02 1.065684e+00 -4.758047e-02 8.218931e-02 -4.758047e-02 -2.733273e+01
1.034430e+00 5.055142e-02 2.968229e-01 5.055142e-02 5.457636e-01 5.055142e-02 -2.639402e+01
5.826416e-01 -1.074587e-01 2.061789e-01 -1.074587e-01 -4.650944e-01 -1.074587e-01 -8.045167e+01
1.457277e-01 6.749625e-02 4.043666e-01 6.749625e-02 -8.500097e-01 6.749625e-02 -4.508928e+01
7.036980e-02 -3.700545e-02 1.642709e+00 -3.700545e-02 9.810573e-02 -3.700545e-02 -1.742303e+01
6.568612e-01 -3.725213e-02 -4.530174e-01 -3.725213e-02 -5.731572e-01 -3.725213e-02 -6.895053e+01
4.291094e-02 8.098445e-03 1.816126e-01 8.098445e-03 -1.972566e-02 8.098445e-03 -1.845467e+01
4.224093e-02 2.712163e-03 3.576262e-01 2.712163e-03 -3.615675e-02 2.712163e-03 -2.736019e+00
7.746138e-01 -3.269082e-02 -3.546063e-02 -3.269082e-02 -2.544120e-01 -3.269082e-02 -6.038322e+01
1.527755e-01 -2.370720e-02 -2.402400e-01 -2.370720e-02 -2.841807e-01 -2.370720e-02 -2.666874e+01
[ getOption("max.print") est atteint -- 20 lignes omises ]
Model rank = 10417 / 10417
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00e+00 6.86e+00 1.02 0.930
s(f0Zscore2) 9.00e+00 1.00e+00 1.02 0.870
s(durationZscore2) 2.90e+01 1.00e+00 1.03 0.985
ti(measurement.no,f0Zscore2,durationZscore2) 3.08e+02 6.41e+01 0.94 0.005 **
ti(measurement.no,durationZscore2) 4.40e+01 1.21e+01 0.98 0.135
ti(measurement.no,f0Zscore2) 2.80e+01 1.28e+01 1.02 0.895
ti(f0Zscore2,durationZscore2) 7.70e+01 1.48e+01 1.02 0.805
s(word) 3.19e+02 1.99e+02 NA NA
s(wordPos) 4.66e+02 5.47e+01 NA NA
s(wordLeftRightTone) 4.43e+02 5.28e+01 NA NA
s(measurement.no,wordPos) 4.66e+02 1.61e+02 NA NA
s(f0Zscore2,wordPos) 4.66e+02 9.02e+01 NA NA
s(durationZscore2,wordPos) 4.66e+02 3.48e+01 NA NA
s(measurement.no,wordLeftRightTone) 4.43e+02 1.38e+02 NA NA
s(f0Zscore2,wordLeftRightTone) 4.43e+02 3.69e+01 NA NA
s(durationZscore2,wordLeftRightTone) 4.43e+02 5.47e+00 NA NA
s(measurement.no,word) 3.19e+02 1.21e+02 NA NA
s(f0Zscore2,word) 3.19e+02 5.33e+01 NA NA
s(durationZscore2,word) 3.19e+02 6.72e-04 NA NA
s(measurement.no,speaker) 1.00e+02 2.69e+01 1.02 0.920
s(durationZscore2,speaker) 3.00e+02 2.12e+01 1.03 0.995
s(f0Zscore2,speaker) 1.00e+02 2.27e+00 1.02 0.855
s(measurement.no,speakerPos) 3.00e+02 3.97e+01 1.02 0.935
s(durationZscore2,speakerPos) 9.00e+02 8.71e+01 1.03 0.995
s(f0Zscore2,speakerPos) 3.00e+02 7.66e+01 1.02 0.840
s(measurement.no,speakerLeftRightTone) 6.00e+02 1.54e+02 1.02 0.920
s(durationZscore2,speakerLeftRightTone) 1.80e+03 1.01e+02 1.03 0.995
s(f0Zscore2,speakerLeftRightTone) 6.00e+02 1.19e+02 1.02 0.850
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
# 3D plotting
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2g, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.au.mas$durationZscore2, c(0.25))),
ylim = quantile(data.au.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.25au * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0au + global_mean0au),
transform = function(f2Zscore2) f2Zscore2 * global_sd2au + global_mean2au,
zlim = c(1000, 1400),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.253736 to 1.355745.
* durationZscore2 : numeric predictor; set to the value(s): -0.680380067515762.
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(1000, 1400), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))fvisgam(gamm.model2g, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2. = quantile(data.au.mas$durationZscore2, c(0.5))),
ylim = quantile(data.au.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.5au * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0au + global_mean0au),
transform = function(f2Zscore2) f2Zscore2 * global_sd2au + global_mean2au,
zlim = c(1000, 1400),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.253736 to 1.355745.
* durationZscore2 : numeric predictor; set to the value(s): -0.0990769355270091.
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(1000, 1400), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))fvisgam(gamm.model2g, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.au.mas$durationZscore2, c(0.75))),
ylim = quantile(data.au.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.75au * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0au + global_mean0au),
transform = function(f2Zscore2) f2Zscore2 * global_sd2au + global_mean2au,
zlim = c(1000, 1400),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.253736 to 1.355745.
* durationZscore2 : numeric predictor; set to the value(s): 0.530017553918074.
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(1000, 1400), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)# 3D plotting
png("pred2b-7.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2g, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.au.mas$durationZscore2, c(0.25))),
ylim = quantile(data.au.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.25au * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0au + global_mean0au),
transform = function(f2Zscore2) f2Zscore2 * global_sd2au + global_mean2au,
zlim = c(1000, 1400),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.253736 to 1.355745.
* durationZscore2 : numeric predictor; set to the value(s): -0.680380067515762.
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(1000, 1400), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2g, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2. = quantile(data.au.mas$durationZscore2, c(0.5))),
ylim = quantile(data.au.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.5au * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0au + global_mean0au),
transform = function(f2Zscore2) f2Zscore2 * global_sd2au + global_mean2au,
zlim = c(1000, 1400),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.253736 to 1.355745.
* durationZscore2 : numeric predictor; set to the value(s): -0.0990769355270091.
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(1000, 1400), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2g, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.au.mas$durationZscore2, c(0.75))),
ylim = quantile(data.au.mas$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.75au * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0au + global_mean0au),
transform = function(f2Zscore2) f2Zscore2 * global_sd2au + global_mean2au,
zlim = c(1000, 1400),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.253736 to 1.355745.
* durationZscore2 : numeric predictor; set to the value(s): 0.530017553918074.
* word : factor; set to the value(s): 到. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 到 Med. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 到 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0005. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0004 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0005 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(1000, 1400), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
system.time(gamm.model2h.noAR <- bam(f2Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.au.fem, method="fREML", discrete = TRUE, nthreads = ncores)
)# Auto-regressive model
system.time(gamm.model2h <- bam(f2Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.au.fem, method="fREML", discrete = TRUE, nthreads = ncores, rho = r.gamm.model2h, AR.start = data.au.fem$start)
)
Family: gaussian
Link function: identity
Formula:
f2Zscore2 ~ s(measurement.no, bs = "cr", k = 10) + s(f0Zscore2,
bs = "cr", k = 10) + s(durationZscore2, bs = "cr", k = 30) +
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + ti(measurement.no, durationZscore2,
bs = "cr", k = c(5, 12)) + ti(measurement.no, f0Zscore2,
bs = "cr", k = c(5, 8)) + ti(f0Zscore2, durationZscore2,
bs = "cr", k = c(8, 12)) + s(word, bs = "re") + s(wordPos,
bs = "re") + s(wordLeftRightTone, bs = "re") + s(wordPos,
measurement.no, bs = "re") + s(wordPos, f0Zscore2, bs = "re") +
s(wordPos, durationZscore2, bs = "re") + s(wordLeftRightTone,
measurement.no, bs = "re") + s(wordLeftRightTone, f0Zscore2,
bs = "re") + s(wordLeftRightTone, durationZscore2, bs = "re") +
s(word, measurement.no, bs = "re") + s(word, f0Zscore2, bs = "re") +
s(word, durationZscore2, bs = "re") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speaker, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(measurement.no, speakerPos, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(durationZscore2, speakerPos, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(durationZscore2, speakerLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1)
Parametric coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.02958 0.06649 0.445 0.656
Approximate significance of smooth terms:
edf Ref.df F p-value
s(measurement.no) 7.016 7.459 46.999 < 2e-16 ***
s(f0Zscore2) 1.000 1.000 18.340 1.88e-05 ***
s(durationZscore2) 2.747 2.940 1.431 0.2266
ti(measurement.no,f0Zscore2,durationZscore2) 44.074 64.013 1.320 0.0448 *
ti(measurement.no,durationZscore2) 7.952 10.232 3.701 5.19e-05 ***
ti(measurement.no,f0Zscore2) 10.475 13.895 3.465 1.27e-05 ***
ti(f0Zscore2,durationZscore2) 10.158 13.317 1.485 0.1155
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
R-sq.(adj) = 0.75 Deviance explained = 79.1%
fREML = 7659.6 Scale est. = 0.22268 n = 9332
Method: fREML Optimizer: perf chol
$grad
[1] -3.074910e-08 -3.637654e-05 -1.926216e-06 8.731321e-08 3.519330e-07 -8.500149e-08 1.447793e-08 -7.361485e-08 -1.978111e-08
[10] -1.164051e-07 2.246844e-07 -1.259442e-07 -8.593502e-06 -2.606808e-07 -2.164774e-06 3.054713e-06 -5.065912e-08 -7.266396e-06
[19] 2.538665e-06 5.390557e-07 -1.111610e-06 5.055001e-07 8.653278e-07 -3.596819e-05 1.793014e-08 -5.266526e-05 -9.189334e-05
[28] -5.266526e-05 -5.119083e-05 -5.266526e-05 -7.936636e-07 -1.264994e-07 -8.526895e-06 -1.264992e-07 1.628905e-07 -1.264992e-07
[37] 6.869135e-07 6.390165e-07 -9.524021e-06 6.390161e-07 8.489512e-07 6.390161e-07 1.255051e-04
$hess
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
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-5.631152e-03 3.903702e-07 1.440748e-02 2.054033e+00 4.262546e-01 -3.981307e-01 9.272292e-02 8.893814e-02 -1.253374e-03
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-3.909292e-03 4.570402e-07 -2.473398e-02 -3.981307e-01 5.436040e-01 1.109710e+00 -1.984474e-03 -3.083361e-02 -4.001879e-02
2.621727e-03 -3.047568e-07 2.595891e-03 9.272292e-02 -3.408242e-02 -1.984474e-03 1.049566e+00 9.777025e-02 5.894589e-03
6.175609e-03 -7.420139e-08 1.236304e-02 8.893814e-02 -9.470631e-02 -3.083361e-02 9.777025e-02 1.160625e+00 -2.477564e-02
8.126456e-03 1.305448e-07 8.393302e-04 -1.253374e-03 -1.888229e-02 -4.001879e-02 5.894589e-03 -2.477564e-02 1.157033e+00
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-2.485612e-03 1.015333e-06 -4.559181e-02 4.439917e-02 -8.252614e-02 -1.006966e-02 -1.668288e-03 3.382310e-02 2.130685e-03
-1.262873e-03 1.344682e-06 -9.812693e-03 -1.575377e-03 3.545358e-02 -2.081622e-02 -1.096051e-03 1.904333e-02 1.015311e-02
1.068930e-02 1.288450e-06 8.551100e-02 1.884414e-03 -2.680559e-04 1.245235e-01 1.065589e-02 1.541097e-02 5.340898e-06
-7.008830e-04 -9.181646e-07 -4.617555e-03 -1.011517e-03 8.043250e-04 -2.499413e-02 -4.826454e-03 -2.507136e-03 2.420797e-04
4.768416e-03 -1.940081e-06 -3.117701e-02 2.111386e-02 -3.534657e-02 4.454078e-02 -2.386113e-03 1.205165e-02 1.073177e-03
6.844733e-04 -3.574772e-06 -8.102747e-02 3.033297e-02 -2.682510e-01 -6.197571e-02 3.365899e-02 1.504440e-01 -1.494562e-02
3.430893e-03 2.447680e-06 1.483707e-02 -2.498008e-02 -3.057494e-02 1.007059e-02 1.478827e-02 4.395746e-02 -4.920250e-03
4.350886e-03 1.253294e-06 1.724080e-01 -2.539813e-02 -5.984789e-02 -2.870816e-02 -9.985796e-04 -1.278485e-02 -7.911921e-03
1.720913e-02 -2.726290e-06 -7.500690e-02 3.284903e-02 -8.329645e-02 9.175296e-03 1.686579e-02 2.378991e-02 2.137647e-02
6.873664e-03 5.752131e-08 -5.406769e-03 1.369049e-02 -9.555065e-02 3.118958e-02 8.482350e-03 -1.725988e-03 3.512805e-02
-2.975196e-05 1.057280e-07 -8.102377e-03 -2.891052e-03 -2.301823e-02 -2.095578e-02 2.284902e-04 3.077600e-03 -7.191830e-03
7.809524e-03 1.022572e-06 -1.246575e-02 -5.332421e-03 -2.493703e-02 1.235061e-01 1.720188e-02 6.599437e-02 2.427246e-02
1.264045e-02 4.442951e-06 2.283823e-02 -3.326595e-02 -3.505791e-02 -2.382100e-02 4.569288e-03 8.895433e-03 3.444666e-03
[,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18]
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1.529856e-06 1.015333e-06 1.344682e-06 1.288450e-06 -9.181646e-07 -1.940081e-06 -3.574772e-06 2.447680e-06 1.253294e-06
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-1.562645e-02 4.439917e-02 -1.575377e-03 1.884414e-03 -1.011517e-03 2.111386e-02 3.033297e-02 -2.498008e-02 -2.539813e-02
-2.365951e-02 -8.252614e-02 3.545358e-02 -2.680559e-04 8.043250e-04 -3.534657e-02 -2.682510e-01 -3.057494e-02 -5.984789e-02
-5.479513e-02 -1.006966e-02 -2.081622e-02 1.245235e-01 -2.499413e-02 4.454078e-02 -6.197571e-02 1.007059e-02 -2.870816e-02
7.998057e-03 -1.668288e-03 -1.096051e-03 1.065589e-02 -4.826454e-03 -2.386113e-03 3.365899e-02 1.478827e-02 -9.985796e-04
-4.738889e-03 3.382310e-02 1.904333e-02 1.541097e-02 -2.507136e-03 1.205165e-02 1.504440e-01 4.395746e-02 -1.278485e-02
3.506961e-01 2.130685e-03 1.015311e-02 5.340898e-06 2.420797e-04 1.073177e-03 -1.494562e-02 -4.920250e-03 -7.911921e-03
1.231807e+00 -4.156099e-03 2.782802e-03 -8.552269e-02 1.782634e-02 1.788545e-02 3.168668e-02 4.862505e-03 5.717694e-02
-4.156099e-03 5.653481e-01 1.627182e-01 5.353121e-02 9.585895e-03 1.838587e-02 5.554201e-02 6.203627e-02 -1.885412e-02
2.782802e-03 1.627182e-01 3.662550e-01 1.583657e-02 -5.563460e-03 1.454397e-02 -2.733056e-02 3.618136e-02 5.452826e-03
-8.552269e-02 5.353121e-02 1.583657e-02 9.532817e+01 1.159283e+00 2.729884e+00 -2.582184e+00 9.579803e-01 9.737487e-01
1.782634e-02 9.585895e-03 -5.563460e-03 1.159283e+00 8.605487e-01 1.376037e-02 -6.646631e-01 5.448329e-02 1.958641e-01
1.788545e-02 1.838587e-02 1.454397e-02 2.729884e+00 1.376037e-02 4.254433e+00 -2.032106e-01 1.104507e-01 1.488388e-02
3.168668e-02 5.554201e-02 -2.733056e-02 -2.582184e+00 -6.646631e-01 -2.032106e-01 2.696057e+01 1.797286e-01 -1.265438e-01
4.862505e-03 6.203627e-02 3.618136e-02 9.579803e-01 5.448329e-02 1.104507e-01 1.797286e-01 2.387628e+00 1.487298e-01
5.717694e-02 -1.885412e-02 5.452826e-03 9.737487e-01 1.958641e-01 1.488388e-02 -1.265438e-01 1.487298e-01 6.205983e+00
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-1.486265e-02 5.303797e-03 -6.769704e-03 1.359818e+00 -7.354154e-04 5.418453e-01 2.955080e-01 8.245805e-01 1.353841e-01
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1.668509e-06 7.165533e-07 1.668509e-06 3.421037e-02 8.195610e-03 3.196802e-01 8.195610e-03 2.859951e-02 8.195610e-03
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[,37] [,38] [,39] [,40] [,41] [,42] [,43]
2.340287e-01 1.228208e-03 1.096829e-03 1.228208e-03 3.049599e-03 1.228208e-03 -3.008122e+00
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3.818146e-03 -5.715117e-03 -2.314074e-02 -5.715117e-03 6.060386e-02 -5.715117e-03 -2.077802e+00
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2.325560e-02 9.445433e-03 3.445615e-03 9.445433e-03 -5.200756e-02 9.445433e-03 -2.724800e+00
4.976281e-02 4.534995e-03 -6.956691e-02 4.534995e-03 1.600365e-01 4.534995e-03 -2.207852e+00
1.883068e-02 -5.861526e-04 -3.703327e-02 -5.861526e-04 2.711922e-02 -5.861526e-04 -2.371234e+00
7.006119e-01 -4.929979e-02 3.685132e-01 -4.929979e-02 2.336671e-01 -4.929979e-02 -1.191207e+02
6.367663e-02 -2.404868e-02 -1.633596e-01 -2.404868e-02 -7.050540e-03 -2.404868e-02 -7.828701e+00
8.556506e-01 -1.484905e-02 1.215262e-01 -1.484905e-02 1.147344e-01 -1.484905e-02 -1.431609e+01
4.999794e-01 -1.494489e-02 8.061140e-02 -1.494489e-02 -8.398972e-02 -1.494489e-02 -6.177537e+01
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4.106050e-02 3.054109e-02 1.492015e-01 3.054109e-02 4.087710e-02 3.054109e-02 -4.275921e+00
1.736595e+00 3.102809e-03 1.695624e-01 3.102808e-03 6.970199e-03 3.102808e-03 -7.901454e+01
2.710713e-01 3.752186e-02 -3.349090e-02 3.752186e-02 8.262086e-02 3.752186e-02 -2.211411e+01
[ getOption("max.print") est atteint -- 20 lignes omises ]
Model rank = 10181 / 10181
Basis dimension (k) checking results. Low p-value (k-index<1) may
indicate that k is too low, especially if edf is close to k'.
k' edf k-index p-value
s(measurement.no) 9.00e+00 7.02e+00 0.98 0.070 .
s(f0Zscore2) 9.00e+00 1.00e+00 0.99 0.250
s(durationZscore2) 2.90e+01 2.75e+00 1.00 0.515
ti(measurement.no,f0Zscore2,durationZscore2) 3.08e+02 4.41e+01 0.98 0.075 .
ti(measurement.no,durationZscore2) 4.40e+01 7.95e+00 1.01 0.820
ti(measurement.no,f0Zscore2) 2.80e+01 1.05e+01 1.02 0.965
ti(f0Zscore2,durationZscore2) 7.70e+01 1.02e+01 0.99 0.145
s(word) 3.10e+02 2.38e+02 NA NA
s(wordPos) 4.62e+02 1.57e+01 NA NA
s(wordLeftRightTone) 4.22e+02 2.86e+01 NA NA
s(measurement.no,wordPos) 4.62e+02 1.24e+02 NA NA
s(f0Zscore2,wordPos) 4.62e+02 3.55e+01 NA NA
s(durationZscore2,wordPos) 4.62e+02 4.17e+01 NA NA
s(measurement.no,wordLeftRightTone) 4.22e+02 1.13e+02 NA NA
s(f0Zscore2,wordLeftRightTone) 4.22e+02 5.11e+01 NA NA
s(durationZscore2,wordLeftRightTone) 4.22e+02 8.55e+00 NA NA
s(measurement.no,word) 3.10e+02 1.58e+02 NA NA
s(f0Zscore2,word) 3.10e+02 4.42e+01 NA NA
s(durationZscore2,word) 3.10e+02 3.23e-04 NA NA
s(measurement.no,speaker) 1.00e+02 3.07e+01 0.98 0.075 .
s(durationZscore2,speaker) 3.00e+02 9.76e-04 1.00 0.565
s(f0Zscore2,speaker) 1.00e+02 7.65e-04 0.99 0.265
s(measurement.no,speakerPos) 3.00e+02 6.93e+01 0.98 0.115
s(durationZscore2,speakerPos) 9.00e+02 8.06e+01 1.00 0.555
s(f0Zscore2,speakerPos) 3.00e+02 5.73e+01 0.99 0.320
s(measurement.no,speakerLeftRightTone) 5.80e+02 1.53e+02 0.98 0.090 .
s(durationZscore2,speakerLeftRightTone) 1.74e+03 8.92e+01 1.00 0.535
s(f0Zscore2,speakerLeftRightTone) 5.80e+02 1.05e+02 0.99 0.330
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
# 3D plotting
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2h, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.au.fem$durationZscore2, c(0.25))),
ylim = quantile(data.au.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.25auf * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0auf + global_mean0auf),
transform = function(f2Zscore2) f2Zscore2 * global_sd2auf + global_mean2auf,
zlim = c(1100, 1600),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.270026 to 1.307646.
* durationZscore2 : numeric predictor; set to the value(s): -0.65512883823603.
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(1100, 1600), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))fvisgam(gamm.model2h, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2. = quantile(data.au.fem$durationZscore2, c(0.5))),
ylim = quantile(data.au.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.5auf * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0auf + global_mean0auf),
transform = function(f2Zscore2) f2Zscore2 * global_sd2auf + global_mean2auf,
zlim = c(1100, 1600),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.270026 to 1.307646.
* durationZscore2 : numeric predictor; set to the value(s): -0.135002585755248.
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(1100, 1600), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))fvisgam(gamm.model2h, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.au.fem$durationZscore2, c(0.75))),
ylim = quantile(data.au.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
transform.view = c(function(measurement.no) measurement.no * duration0.75auf * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0auf + global_mean0auf),
transform = function(f2Zscore2) f2Zscore2 * global_sd2auf + global_mean2auf,
zlim = c(1100, 1600),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 30 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 30 values ranging from -1.270026 to 1.307646.
* durationZscore2 : numeric predictor; set to the value(s): 0.536034051323852.
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [31] is not a sub-multiple or multiple of the number of rows [30]
gradientLegend(valRange=c(1100, 1600), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)# 3D plotting
png("pred2b-10.png", width = 6, height = 4, units = "in", res = 1000)
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2h, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.au.fem$durationZscore2, c(0.25))),
ylim = quantile(data.au.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.25auf * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0auf + global_mean0auf),
transform = function(f2Zscore2) f2Zscore2 * global_sd2auf + global_mean2auf,
zlim = c(1100, 1600),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.270026 to 1.307646.
* durationZscore2 : numeric predictor; set to the value(s): -0.65512883823603.
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(1100, 1600), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2h, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2. = quantile(data.au.fem$durationZscore2, c(0.5))),
ylim = quantile(data.au.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.5auf * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0auf + global_mean0auf),
transform = function(f2Zscore2) f2Zscore2 * global_sd2auf + global_mean2auf,
zlim = c(1100, 1600),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.270026 to 1.307646.
* durationZscore2 : numeric predictor; set to the value(s): -0.135002585755248.
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(1100, 1600), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
par(mfrow=c(1,1), cex=1, mar=c(3,3.5,1.5,3.5), mgp=c(2,0.75,0))
fvisgam(gamm.model2h, view=c("measurement.no","f0Zscore2"),
cond = list(durationZscore2 = quantile(data.au.fem$durationZscore2, c(0.75))),
ylim = quantile(data.au.fem$f0Zscore2, c(0.1,0.9), na.rm = T),
n.grid = 100,
transform.view = c(function(measurement.no) measurement.no * duration0.75auf * 0.1, function(f0Zscore2) f0Zscore2 * global_sd0auf + global_mean0auf),
transform = function(f2Zscore2) f2Zscore2 * global_sd2auf + global_mean2auf,
zlim = c(1100, 1600),
hide.label = TRUE, add.color.legend = FALSE, rm.ranef = T, main = "", xlab = "Time (ms)", ylab = "F0 (Hz)",font.lab = 2, cex.lab = 1.3, cex.axis = 1.3, xaxt = "n", color = mapcols_pastel, xaxt = "n")Summary:
* measurement.no : numeric predictor; with 100 values ranging from 0.000000 to 10.000000.
* f0Zscore2 : numeric predictor; with 100 values ranging from -1.270026 to 1.307646.
* durationZscore2 : numeric predictor; set to the value(s): 0.536034051323852.
* word : factor; set to the value(s): 报道. (Might be canceled as random effect, check below.)
* wordPos : factor; set to the value(s): 报道 Fin. (Might be canceled as random effect, check below.)
* wordLeftRightTone : factor; set to the value(s): 报道 L H. (Might be canceled as random effect, check below.)
* speaker : factor; set to the value(s): S0133. (Might be canceled as random effect, check below.)
* speakerPos : factor; set to the value(s): S0129 Fin. (Might be canceled as random effect, check below.)
* speakerLeftRightTone : factor; set to the value(s): S0125 L H. (Might be canceled as random effect, check below.)
* NOTE : The following random effects columns are canceled: s(word),s(wordPos),s(wordLeftRightTone),s(measurement.no,wordPos),s(f0Zscore2,wordPos),s(durationZscore2,wordPos),s(measurement.no,wordLeftRightTone),s(f0Zscore2,wordLeftRightTone),s(durationZscore2,wordLeftRightTone),s(measurement.no,word),s(f0Zscore2,word),s(durationZscore2,word),s(measurement.no,speaker),s(durationZscore2,speaker),s(f0Zscore2,speaker),s(measurement.no,speakerPos),s(durationZscore2,speakerPos),s(f0Zscore2,speakerPos),s(measurement.no,speakerLeftRightTone),s(durationZscore2,speakerLeftRightTone),s(f0Zscore2,speakerLeftRightTone)
* Note: Transformation function(s) applied to values of x-axis and / or y-axis.
Avis : data length [101] is not a sub-multiple or multiple of the number of rows [100]
gradientLegend(valRange=c(1100, 1600), length=.5, pos=.75, side=4, n.seg = 1, inside=FALSE,font = 1, cex = 1, color = mapcols_pastel)
axis(1, at=tickvals2, labels=ticknames2, las=2, cex.axis=1)
dev.off()null device
1
We take data.ai.mas as the sample data set, Z scored F1
as the prediction. The purpose of model comparison section is to
investigate whether incorporating relevant variables (predictors or
random effects) leads to a significant enhancement in model
performance.
With only speaker as the random effect.
system.time(REspeaker <- bam(f1Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.ai.mas, method="fREML", discrete = TRUE, nthreads = ncores)
) utilisateur système écoulé
71.378 3.443 7.261
Add the cross effect: speaker*LeftRightTone.
system.time(REspeakerLeftRightTone <- bam(f1Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.ai.mas, method="fREML", discrete = TRUE, nthreads = ncores)
) utilisateur système écoulé
1041.011 8.183 117.364
Add the the cross effect: speaker*Pos.
system.time(REspeakerPos <- bam(f1Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.ai.mas, method="fREML", discrete = TRUE, nthreads = ncores)
) Add the random intercept and random slope of word.
system.time(REword <- bam(f1Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.ai.mas, method="fREML", discrete = TRUE, nthreads = ncores)
) Add the cross effect word*pos and word*LeftRightTone.
This is the final full model.
REfullmodel <- bam(f1Zscore2 ~
# smooth
s(measurement.no, bs="cr", k = 10) +
s(f0Zscore2, bs="cr", k = 10) +
s(durationZscore2, bs="cr", k = 30) +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr", k = c(5, 8, 12)) +
ti(measurement.no, durationZscore2, bs = "cr", k = c(5, 12)) +
ti(measurement.no, f0Zscore2, bs = "cr", k = c(5, 8)) +
ti(f0Zscore2, durationZscore2, bs = "cr", k = c(8, 12)) +
# random effect
s(word, bs="re") +
s(wordPos, bs="re") +
s(wordLeftRightTone, bs="re") +
s(wordPos, measurement.no, bs = "re") +
s(wordPos, f0Zscore2, bs="re") +
s(wordPos, durationZscore2, bs="re") +
s(wordLeftRightTone, measurement.no, bs = "re") +
s(wordLeftRightTone, f0Zscore2, bs="re") +
s(wordLeftRightTone, durationZscore2, bs="re") +
s(word, measurement.no, bs = "re") +
s(word, f0Zscore2, bs="re") +
s(word, durationZscore2, bs="re") +
s(measurement.no, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speaker, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speaker, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerPos, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(measurement.no, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1) +
s(durationZscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=30, m=1) +
s(f0Zscore2, speakerLeftRightTone, bs="fs", xt = list(bs="tp"), k=10, m=1),
data=data.ai.mas, method="fREML", discrete = TRUE, nthreads = ncores)REword: f1Zscore2 ~ s(measurement.no, bs = "cr", k = 10) + s(f0Zscore2,
bs = "cr", k = 10) + s(durationZscore2, bs = "cr", k = 30) +
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + ti(measurement.no, durationZscore2,
bs = "cr", k = c(5, 12)) + ti(measurement.no, f0Zscore2,
bs = "cr", k = c(5, 8)) + ti(f0Zscore2, durationZscore2,
bs = "cr", k = c(8, 12)) + s(word, bs = "re") + s(word, measurement.no,
bs = "re") + s(word, f0Zscore2, bs = "re") + s(word, durationZscore2,
bs = "re") + s(measurement.no, speaker, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(durationZscore2, speaker, bs = "fs", xt = list(bs = "tp"),
k = 30, m = 1) + s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(measurement.no, speakerPos, bs = "fs",
xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speakerPos, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speakerPos, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(measurement.no, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 30,
m = 1) + s(f0Zscore2, speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1)
REfullmodel: f1Zscore2 ~ s(measurement.no, bs = "cr", k = 10) + s(f0Zscore2,
bs = "cr", k = 10) + s(durationZscore2, bs = "cr", k = 30) +
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + ti(measurement.no, durationZscore2,
bs = "cr", k = c(5, 12)) + ti(measurement.no, f0Zscore2,
bs = "cr", k = c(5, 8)) + ti(f0Zscore2, durationZscore2,
bs = "cr", k = c(8, 12)) + s(word, bs = "re") + s(wordPos,
bs = "re") + s(wordLeftRightTone, bs = "re") + s(wordPos,
measurement.no, bs = "re") + s(wordPos, f0Zscore2, bs = "re") +
s(wordPos, durationZscore2, bs = "re") + s(wordLeftRightTone,
measurement.no, bs = "re") + s(wordLeftRightTone, f0Zscore2,
bs = "re") + s(wordLeftRightTone, durationZscore2, bs = "re") +
s(word, measurement.no, bs = "re") + s(word, f0Zscore2, bs = "re") +
s(word, durationZscore2, bs = "re") + s(measurement.no, speaker,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speaker, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(measurement.no, speakerPos, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(durationZscore2, speakerPos, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerPos,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(measurement.no,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(durationZscore2, speakerLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 30, m = 1) + s(f0Zscore2, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1)
Chi-square test of fREML scores
-----
AIC difference: 1216.69, model REfullmodel has lower AIC.
REspeakerPos: f1Zscore2 ~ s(measurement.no, bs = "cr", k = 10) + s(f0Zscore2,
bs = "cr", k = 10) + s(durationZscore2, bs = "cr", k = 30) +
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + ti(measurement.no, durationZscore2,
bs = "cr", k = c(5, 12)) + ti(measurement.no, f0Zscore2,
bs = "cr", k = c(5, 8)) + ti(f0Zscore2, durationZscore2,
bs = "cr", k = c(8, 12)) + s(measurement.no, speaker, bs = "fs",
xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speaker, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(measurement.no, speakerLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 30,
m = 1) + s(f0Zscore2, speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(measurement.no, speakerPos, bs = "fs",
xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speakerPos, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speakerPos, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1)
REword: f1Zscore2 ~ s(measurement.no, bs = "cr", k = 10) + s(f0Zscore2,
bs = "cr", k = 10) + s(durationZscore2, bs = "cr", k = 30) +
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + ti(measurement.no, durationZscore2,
bs = "cr", k = c(5, 12)) + ti(measurement.no, f0Zscore2,
bs = "cr", k = c(5, 8)) + ti(f0Zscore2, durationZscore2,
bs = "cr", k = c(8, 12)) + s(word, bs = "re") + s(word, measurement.no,
bs = "re") + s(word, f0Zscore2, bs = "re") + s(word, durationZscore2,
bs = "re") + s(measurement.no, speaker, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(durationZscore2, speaker, bs = "fs", xt = list(bs = "tp"),
k = 30, m = 1) + s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(measurement.no, speakerPos, bs = "fs",
xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speakerPos, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speakerPos, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(measurement.no, speakerLeftRightTone,
bs = "fs", xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 30,
m = 1) + s(f0Zscore2, speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1)
Chi-square test of fREML scores
-----
AIC difference: 2565.29, model REword has lower AIC.
REspeakerLeftRightTone: f1Zscore2 ~ s(measurement.no, bs = "cr", k = 10) + s(f0Zscore2,
bs = "cr", k = 10) + s(durationZscore2, bs = "cr", k = 30) +
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + ti(measurement.no, durationZscore2,
bs = "cr", k = c(5, 12)) + ti(measurement.no, f0Zscore2,
bs = "cr", k = c(5, 8)) + ti(f0Zscore2, durationZscore2,
bs = "cr", k = c(8, 12)) + s(measurement.no, speaker, bs = "fs",
xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speaker, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(measurement.no, speakerLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 30,
m = 1) + s(f0Zscore2, speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1)
REspeakerPos: f1Zscore2 ~ s(measurement.no, bs = "cr", k = 10) + s(f0Zscore2,
bs = "cr", k = 10) + s(durationZscore2, bs = "cr", k = 30) +
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + ti(measurement.no, durationZscore2,
bs = "cr", k = c(5, 12)) + ti(measurement.no, f0Zscore2,
bs = "cr", k = c(5, 8)) + ti(f0Zscore2, durationZscore2,
bs = "cr", k = c(8, 12)) + s(measurement.no, speaker, bs = "fs",
xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speaker, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(measurement.no, speakerLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 30,
m = 1) + s(f0Zscore2, speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1) + s(measurement.no, speakerPos, bs = "fs",
xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speakerPos, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speakerPos, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1)
Chi-square test of fREML scores
-----
AIC difference: 1281.25, model REspeakerPos has lower AIC.
REspeaker: f1Zscore2 ~ s(measurement.no, bs = "cr", k = 10) + s(f0Zscore2,
bs = "cr", k = 10) + s(durationZscore2, bs = "cr", k = 30) +
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + ti(measurement.no, durationZscore2,
bs = "cr", k = c(5, 12)) + ti(measurement.no, f0Zscore2,
bs = "cr", k = c(5, 8)) + ti(f0Zscore2, durationZscore2,
bs = "cr", k = c(8, 12)) + s(measurement.no, speaker, bs = "fs",
xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speaker, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1)
REspeakerLeftRightTone: f1Zscore2 ~ s(measurement.no, bs = "cr", k = 10) + s(f0Zscore2,
bs = "cr", k = 10) + s(durationZscore2, bs = "cr", k = 30) +
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr",
k = c(5, 8, 12)) + ti(measurement.no, durationZscore2,
bs = "cr", k = c(5, 12)) + ti(measurement.no, f0Zscore2,
bs = "cr", k = c(5, 8)) + ti(f0Zscore2, durationZscore2,
bs = "cr", k = c(8, 12)) + s(measurement.no, speaker, bs = "fs",
xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speaker, bs = "fs", xt = list(bs = "tp"), k = 30, m = 1) +
s(f0Zscore2, speaker, bs = "fs", xt = list(bs = "tp"), k = 10,
m = 1) + s(measurement.no, speakerLeftRightTone, bs = "fs",
xt = list(bs = "tp"), k = 10, m = 1) + s(durationZscore2,
speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"), k = 30,
m = 1) + s(f0Zscore2, speakerLeftRightTone, bs = "fs", xt = list(bs = "tp"),
k = 10, m = 1)
Chi-square test of fREML scores
-----
AIC difference: 3652.24, model REspeakerLeftRightTone has lower AIC.
Here we don’t specify k-values since it will cause errors.
This is the fundamental structure: only normalized time.
system.time(fullmodel <- bam(f1Zscore2 ~
# smooth
s(measurement.no, bs="cr") +
s(f0Zscore2, bs="cr") +
s(durationZscore2, bs="cr") +
# interaction between smooths
ti(measurement.no, f0Zscore2, durationZscore2, bs = "cr") +
ti(measurement.no, durationZscore2, bs = "cr") +
ti(measurement.no, f0Zscore2, bs = "cr") +
ti(f0Zscore2, durationZscore2, bs = "cr"),
data=data.ai.mas, method="ML", discrete = TRUE, nthreads = ncores)
) removeduration: f1Zscore2 ~ s(measurement.no, bs = "cr") + s(f0Zscore2, bs = "cr") +
ti(measurement.no, f0Zscore2, bs = "cr")
fullmodel: f1Zscore2 ~ s(measurement.no, bs = "cr") + s(f0Zscore2, bs = "cr") +
s(durationZscore2, bs = "cr") + ti(measurement.no, f0Zscore2,
durationZscore2, bs = "cr") + ti(measurement.no, durationZscore2,
bs = "cr") + ti(measurement.no, f0Zscore2, bs = "cr") + ti(f0Zscore2,
durationZscore2, bs = "cr")
Chi-square test of ML scores
-----
AIC difference: 311.33, model fullmodel has lower AIC.
duration is significant
removef0: f1Zscore2 ~ s(measurement.no, bs = "cr") + s(durationZscore2,
bs = "cr") + ti(measurement.no, durationZscore2, bs = "cr")
fullmodel: f1Zscore2 ~ s(measurement.no, bs = "cr") + s(f0Zscore2, bs = "cr") +
s(durationZscore2, bs = "cr") + ti(measurement.no, f0Zscore2,
durationZscore2, bs = "cr") + ti(measurement.no, durationZscore2,
bs = "cr") + ti(measurement.no, f0Zscore2, bs = "cr") + ti(f0Zscore2,
durationZscore2, bs = "cr")
Chi-square test of ML scores
-----
AIC difference: 3440.09, model fullmodel has lower AIC.
f0 is significant
removedurationandf0: f1Zscore2 ~ s(measurement.no, bs = "cr")
removef0: f1Zscore2 ~ s(measurement.no, bs = "cr") + s(durationZscore2,
bs = "cr") + ti(measurement.no, durationZscore2, bs = "cr")
Chi-square test of ML scores
-----
AIC difference: 240.25, model removef0 has lower AIC.
duration is significant
removedurationandf0: f1Zscore2 ~ s(measurement.no, bs = "cr")
removeduration: f1Zscore2 ~ s(measurement.no, bs = "cr") + s(f0Zscore2, bs = "cr") +
ti(measurement.no, f0Zscore2, bs = "cr")
Chi-square test of ML scores
-----
AIC difference: 3369.00, model removeduration has lower AIC.
f0 is significant
R version 4.4.2 (2024-10-31)
Platform: x86_64-pc-linux-gnu
Running under: Rocky Linux 8.10 (Green Obsidian)
Matrix products: default
BLAS: /opt/R/4.4.2/lib64/R/lib/libRblas.so
LAPACK: /opt/R/4.4.2/lib64/R/lib/libRlapack.so; LAPACK version 3.12.0
locale:
[1] LC_CTYPE=fr_FR.UTF-8 LC_NUMERIC=C LC_TIME=fr_FR.UTF-8 LC_COLLATE=fr_FR.UTF-8 LC_MONETARY=fr_FR.UTF-8
[6] LC_MESSAGES=fr_FR.UTF-8 LC_PAPER=fr_FR.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=fr_FR.UTF-8 LC_IDENTIFICATION=C
time zone: Europe/Paris
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] colorspace_2.1-1 phonR_1.0-7 itsadug_2.4.1 plotfunctions_1.4 mgcv_1.9-1 ggpubr_0.6.0 scales_1.3.0
[8] nlme_3.1-166 lubridate_1.9.3 forcats_1.0.0 stringr_1.5.1 dplyr_1.1.4 purrr_1.0.2 readr_2.1.5
[15] tidyr_1.3.1 tibble_3.2.1 ggplot2_3.5.1 tidyverse_2.0.0
loaded via a namespace (and not attached):
[1] sass_0.4.9 utf8_1.2.4 generics_0.1.3 rstatix_0.7.2 stringi_1.8.4 lattice_0.22-6 hms_1.1.3
[8] digest_0.6.37 magrittr_2.0.3 timechange_0.3.0 evaluate_1.0.1 grid_4.4.2 fastmap_1.2.0 jsonlite_1.8.9
[15] Matrix_1.7-1 backports_1.5.0 Formula_1.2-5 fansi_1.0.6 jquerylib_0.1.4 abind_1.4-8 cli_3.6.3
[22] rlang_1.1.4 munsell_0.5.1 splines_4.4.2 yaml_2.3.10 withr_3.0.2 cachem_1.1.0 colorRamps_2.3.4
[29] tools_4.4.2 tzdb_0.4.0 ggsignif_0.6.4 broom_1.0.7 vctrs_0.6.5 R6_2.5.1 lifecycle_1.0.4
[36] car_3.1-3 pkgconfig_2.0.3 pillar_1.9.0 bslib_0.8.0 gtable_0.3.6 rsconnect_1.3.2 glue_1.8.0
[43] xfun_0.49 tidyselect_1.2.1 rstudioapi_0.17.1 knitr_1.48 htmltools_0.5.8.1 rmarkdown_2.29 carData_3.0-5
[50] compiler_4.4.2